Curriculum Vitae - Delab Engineeringdelab.csd.auth.gr › ~tiakas › CVtiakas2019.pdf · Curriculum Vitae PERSONAL INFORMATION Full name: Eleftherios Tiakas Date / Place of birth:

Curriculum Vitae

PERSONAL INFORMATION

Full name: Eleftherios Tiakas

Date / Place of birth: 28/11/1972, Thessaloniki

Marital status: Married, 1 child

Military service: Fulfilled

Current position: Laboratory Teaching Staff

Department: Department of Informatics

University: Aristotle University of Thessaloniki (AUTH)

Work address: Data Engineering Laboratory, Department of

Informatics, AUTH, 54124, Greece

e-mail: [email protected]

URL: http://delab.csd.auth.gr/~tiakas/

BRIEF DESCRIPTION OF UNIVERSITY CAREER

I have received B.Sc. in Mathematics in 1994 from the Department of Mathematics, Faculty of

Sciences, Aristotle University of Thessaloniki. In 2004 I was appointed by the Ministry of

Education, through Supreme Council for Civil Personnel Selection, as a permanent Teacher of

Mathematics in Secondary Education. In 2006 I received a B.Sc. in Computer Science –

Informatics and a M.Sc. in Computer Science with focus on Information Systems. In 2011 I

received a Ph.D. from the Department of Informatics, Faculty of Sciences, Aristotle University of

Thessaloniki. From 2011 to 2017 I have been a postdoctoral researcher and adjunct lecturer

contracted in the Department of Informatics, AUTH. From 2017 until now I am in the Laboratory

Teaching Staff of the Department of Informatics, AUTH.

My areas of research interest include: Query Processing, Indexing, Databases, Spatial and

Multidimensional Databases, Data Structures, Data Mining, Information Retrieval, Similarity

Search, Social Networks, Bio-Informatics. I am the author of two theses (M.Sc. and Ph.D.). I am

the author/co-author of 12 articles published in international journals, 17 papers published in

international conference proceedings, 2 book chapters, and 3 technical reports. My publications

have already received over 450 citations from other scientific publications. I participated in 11

research projects/and programs funded by the European Union and Greece. Also, I was

responsible for supervising 2 theses during my PhD, and 3 postgraduate theses after. Finally,

from 2007 until now, I also serve as a regular/external reviewer and PC-Member in several

international journals and conferences.

EDUCATION

2005-2011: Ph.D. Diploma from the Department of Informatics, AUTH, with excellent

grade. Ph.D. thesis: “Similarity and domination query processing in

multidimensional spaces”.

2004-2006: M.Sc. Diploma in Computer Science with focus on Information Systems

(CSIS), Department of Informatics, AUTH, and excellent grade: 9.43 / 10.

Postgraduate thesis: “Trajectory similarity queries in spatial networks”.

2004-2006: B.Sc. Diploma in Computer Science with focus on Information Systems

(CSIS), Department of Informatics, AUTH, and excellent grade: 8.72 / 10.

Thesis: “Computing trajectories similarity with metric relations and applications

of range queries in spatial networks”.

1990-1994: B.Sc. Diploma in Mathematics with focus on Applied Mathematics,

Department of Mathematics, AUTH, and excellent grade: 8.56 / 10.

http://www.csd.auth.gr/

http://www.csd.auth.gr/

http://delab.csd.auth.gr/

http://delab.csd.auth.gr/

mailto:[email protected]

http://delab.csd.auth.gr/~tiakas/

Languages

English (BULATS Certificate Β2).

RESEARCH INTERESTS

Big Data, Databases, Data Structures, Query Processing Algorithms, Indexing Structures, Spatial

and Multidimensional Databases, Spatial Databases, Multimedia Databases, Information Systems,

Data Mining, Information Retrieval, Similarity Search, Social Networks, Bio-Informatics, Medical

research, Algorithm Design and Analysis, Discrete Mathematics, Decision Support Systems, GIS,

Forest Modelling, Computational Geometry.

UNIVERSITY TEACHING EXPERIENCE

Spring 2019: Adjunct Lecturer (Laboratory Teaching Staff) of the postgraduate course:

“Advanced Topics in Databases”, Department of Informatics, AUTH.

Spring 2019: Teaching Assistant (Laboratory Teaching Staff) for the undergraduate course:

“Data Structures” of the 2nd

semester, Department of Informatics, AUTH.


“Algorithms” of the 4th


Fall 2018: Adjunct Lecturer (Laboratory Teaching Staff) of the joint postgraduate course:

“Databases”, Department of Informatics, AUTH.

Fall 2018: Teaching Assistant (Laboratory Teaching Staff) for the undergraduate course:

“Databases” of the 5th



“Discrete Mathematics” of the 1st semester, Department of Informatics, AUTH.


“Operating Systems” of the 5th


Spring 2018: Adjunct Lecturer (Laboratory Teaching Staff) of the joint postgraduate course:

“Databases and Data mining”, Department of Informatics, AUTH.





“Algorithms” of the 4th


Fall 2017: Adjunct Lecturer (Laboratory Teaching Staff) of the postgraduate course: “Spatial

and Multimedia Databases”, Department of Informatics, AUTH.


“Databases” of the 5th



“Discrete Mathematics” of the 1st semester, Department of Informatics, AUTH.


“Operating Systems” of the 5th


Spring 2017: Adjunct Lecturer (contracted) of the joint postgraduate course: “Databases and

Data mining”, Department of Informatics, AUTH.

Spring 2017: Adjunct Lecturer (contracted according to the Presidential Decree 407/80 from

11-02-2017 to 30-06-2017) for co-teaching of 1 hour per week of the undergraduate course:



Fall 2016: Adjunct Lecturer (contracted) of the postgraduate course: “Spatial and Multimedia

Databases”, Department of Informatics, AUTH.

Fall 2016: Adjunct Lecturer (contracted according to the Presidential Decree 407/80 from 15-

12-2016 to 10-02-2017) for co-teaching of 2 hours per week of the undergraduate course:

“Basic Programming Principles” of the 1st semester, Department of Informatics, AUTH.

Fall 2016: Teaching Assistant for the undergraduate course: “Databases” of the 5th

semester,

Department of Informatics, AUTH.


semester,


Spring 2015: Adjunct Lecturer (contracted) of the postgraduate course: “Advanced Data

Indexing”, Department of Informatics, AUTH.


semester,



semester,


PUBLICATIONS

1. Journal Articles

[J12] Dimitris Zianis, Gavriil Spyroglou, Eleftherios Tiakas, Kalliopi Radoglou. "Bayesian and

classical models to predict aboveground tree biomass allometry", Forest Science Journal, vol. 62,

no. 3, pp. 247-259, June 2016.

[J11] Eleftherios Tiakas, George Valkanas, Apostolos N. Papadopoulos, Yannis Manolopoulos,

Dimitrios Gunopulos. "Processing Top-k Dominating Queries in Metric Spaces", Transactions on

Database Systems (ACM), vol. 40, no. 4, 38 pages, article 23, January 2016.

[J10] Zaigham Faraz Siddiqui, Eleftherios Tiakas, Panagiotis Symeonidis, Myra Spiliopoulou,

Yannis Manolopoulos. "Learning Relational User Profiles and Recommending Items as Their

Preferences Change", International Journal on Artificial Intelligence Tools (World Scientific

Publishing Company), vol. 24, no. 2, 31 pages, April 2015.

[J9] Nantia Iakovidou, Eleftherios Tiakas, Konstantinos Tsichlas, Yannis Manolopoulos. "Going

over the three dimensional protein structure similarity problem", Artificial Intelligence Review

(Springer), vol. 42, no. 3, pp. 445-459, October 2014.

[J8] Panagiotis Symeonidis, Eleftherios Tiakas. "Transitive node similarity: predicting and

recommending links in signed social networks", World Wide Web Journal (Springer), vol. 17, no. 4,

pp. 743-776, July 2014.

[J7] Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "On Estimating the

Maximum Domination Value and the Skyline Cardinality of Multi-Dimensional Data Sets",

International Journal of Knowledge-Based Organizations (IGI Global), vol. 3, no. 4, pp. 61-83,

October 2013.

[J6] Eleftherios Tiakas, Dimitrios Rafailidis, Anastasios Dimou, Petros Daras. "MSIDX: Multi-

Sort Indexing for Efficient Content-Based Image Search and Retrieval", Transactions on

Multimedia (IEEE), vol. 15, no. 6, pp. 1415-1430, October 2013.

[J5] Panagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos. "A unified framework for

link and rating prediction in multi-modal social networks", International Journal of Social Network

Mining (Inderscience), vol. 1, no. 3/4, pp. 225-253, January 2013.

[J4] Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Progressive

processing of subspace dominating queries", The VLDB Journal (Springer), vol. 20, no. 6, pp. 921-

948, December 2011.

[J3] Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos. "Node and edge selectivity estimation for range queries in spatial networks",

Information Systems (Elsevier), vol. 34, no. 3, pp. 328-352, May 2009.

[J2] Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos, Dragan Stojanovic, Slobodanka Djordjevic-Kajan. "Searching for similar

trajectories in spatial networks", Journal of System and Software (Elsevier), vol. 82, no. 5, pp. 772-

788, May 2009.

[J1] Eleftherios Tiakas, Stefanos Ougiaroglou, Petros Nicopolitidis. "Efficient algorithms for

constructing broadcast disks programs in asymmetric communication environments",

Telecommunication Systems (Springer), vol. 41, no. 3, pp. 185-209, May 2009.

2. Papers in Conference Proceedings

[C17] Theodoros Tzouramanis, Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis

Manolopoulos. "The Range Skyline Query", Proceedings of the 27th International Conference on

Information and Knowledge Management (ACM / CIKM), pp. 47-56, Torino, Italy, October 2018.

[C16] Nikolaos Georgiadis, Eleftherios Tiakas, Yannis Manolopoulos. "Detecting Intrinsic

Dissimilarities in Large Image Databases through Skylines", Proceedings of the 9th International

Conference on Management of Digital EcoSystems (ACM / MEDES), pp.194-201, Bangkok,

Thailand, November 2017, [Best Paper Award].

[C15] Alexander Tzanakas, Eleftherios Tiakas, Yannis Manolopoulos. "Skyline Algorithms on

Streams of Multidimensional Data", Proceedings of the 20th East-European Conference on

Advances in Databases and Information Systems (Springer / ADBIS), pp. 63-71, Prague, Czech

Republic, August 2016.

[C14] Eleftherios Tiakas, Dimitrios Rafailidis. "Scalable Trajectory Similarity Search Based on

Locations in Spatial Networks", Proceedings of the 5th International Conference on Model and

Data Engineering (Springer / MEDI), LNCS vol. 9344, pp. 213-224, Rhodes, Greece, September

2015.

[C13] Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Skyline Queries:

an Introduction (invited)", Proceedings of the 6th International Conference on Information,

Intelligence, Systems & Applications (IISA), 6 pages, Corfu, Greece, July 2015.

[C12] Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Top-k Dominating

Queries: a Survey (invited)", Proceedings of the 17th International Symposium on Programming

and Systems (ISPS), 10 pages, Algiers, Algeria, April 2015.

[C11] Zaigham Faraz Siddiqui, Eleftherios Tiakas, Panagiotis Symeonidis, Myra Spiliopoulou,

Yannis Manolopoulos. "xStreams: Recommending Items to Users with Time-evolving

Preferences", Proceedings of the 4th International Conference on Web Intelligence, Mining and

Semantics (ACM / WIMS), Article 22, 12 pages, Thessaloniki, Greece, June 2014.

[C10] Eleftherios Tiakas, George Valkanas, Apostolos N. Papadopoulos, Yannis Manolopoulos,

Dimitrios Gunopulos: "Metric-Based Top-k Dominating Queries", Proceedings of the 17th

International Conference on Extending Database Technology (Open Proceedings / EDBT), pp. 415-

426, Athens, Greece, March 2014.

[C9] Nantia Iakovidou, Eleftherios Tiakas, Konstantinos Tsichlas: "DISCO: A New Algorithm for

Detecting 3D Protein Structure Similarity", Proceedings of the Artificial Intelligence Applications

and Innovations Workshops (Springer / AIAI), pp. 622-631, Halkidiki, Greece, September 2012.

[C8] Panagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos. "Product recommendation

and rating prediction based on multi-modal social networks", Proceedings of the 5th ACM

Conference on Recommender Systems (ACM / RECSYS), pp. 61-68, Chicago, IL, USA, October

2011.

[C7] Zaigham Faraz Siddiqui, Myra Spiliopoulou, Panagiotis Symeonidis, Eleftherios Tiakas. "A

Data Generator for Multi-Stream Data", Proceedings of the 2nd International Workshop on Mining

Ubiquitous and Social Environments (Springer / MUSE), pp. 63-70, Athens, Greece, September

2011.

[C6] Panagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos. "Transitive node

similarity for link prediction in social networks with positive and negative links", Proceedings of

the 4th ACM Conference on Recommender Systems (ACM / RECSYS), pp. 183-190, Barcelona,

Spain, September 2010.

[C5] Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Estimation of the

Maximum Domination Value in Multi-dimensional Data Sets", Proceedings of the 14th East-

European Conference on Advances in Databases and Information Systems (Springer / ADBIS), pp.

505-519, Novi Sad, Serbia, September 2010.

[C4] Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Graph Node

Clustering via Transitive Node Similarity", Proceedings of the 14th Panhellenic Conference on

Informatics (IEEE / PCI), pp. 72-77, Tripoli, Greece, September 2010.

[C3] Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos. "Selectivity estimation in spatial networks", Proceedings of the 23rd Annual

Symposium on Applied Computing (ACM / SAC), pp. 852-856, Fortaleza, Ceara, Brazil, March

2008.

[C2] Eletherios Tiakas, Stefanos Ougiaroglou, Petros Nicopolitidis. "Efficient broadcast disks

program construction in asymmetric communication environments", Proceedings of the 10th

International Symposium on Modelling, Analysis and Simulation of Wireless and Mobile Systems

(ACM / MSWiM), pp. 279-283, Chania, Crete Island, Greece, October 2007.

[C1] Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos, Dragan Stojanovic, Slobodanka Djordjevic-Kajan. "Trajectory Similarity Search in

Spatial Networks", Proceedings of the 10th International Database Engineering & Applications

Symposium (IEEE / IDEAS), pp. 185-192, Delhi, India, December 2006.

3. Book Chapters

[CH2] Gavriil Spyroglou, Eleftherios Tiakas, Gregor Chatziphilippidis, Vasiliki Kazana. "The

design and use of forest decision support systems in Greece", Computer-based tools for supporting

forest management. The experience and the expertise world-wide (Epsilon Open Archive), pp. 152-

167, 2014.

[CH1] Theodoros Semertzidis, Dimitrios Rafailidis, Eleftherios Tiakas, Michael G. Strintzis,

Petros Daras. "Multimedia Indexing, Search and Retrieval in Large Databases of Social Networks",

Social Media Retrieval, Computer Communications and Networks series (Springer), pp. 43-63,

2012.

4. Technical Reports

[TR3] Nikolaos Georgiadis, Eleftherios Tiakas, Yannis Manolopoulos, Apostolos N.

Papadopoulos. "Skyline-based Dissimilarity of Images", Technical Report, Aristotle University of

Thessaloniki, 2019.

[TR2] Nikolaos Pliakis, Eleftherios Tiakas, Yannis Manolopoulos. "Efficient Progressive

Processing of Trajectories on Road Networks", Technical Report, Aristotle University of

Thessaloniki, 2018.

[TR1] Alexander Tzanakas, Eleftherios Tiakas, Yannis Manolopoulos. "Revisited skyline query

algorithms on streams of multidimensional data", Technical Report, Aristotle University of

Thessaloniki, 2016.

5. Theses

[TH3] Eleftherios Tiakas, “Similarity and domination query processing in multidimensional

spaces”, Ph.D. thesis (in Greek), Department of Informatics, AUTH, 2011.

[TH2] Eleftherios Tiakas, “Trajectory similarity queries in spatial networks”, Postgraduate thesis

(in Greek), Department of Informatics, AUTH, 2006.

[TH1] Eleftherios Tiakas, “Computing trajectory similarity with metric relations and applications

of range queries in spatial networks”, Thesis (in Greek), Department of Informatics, AUTH, 2006.

PARTICIPATION/INVOLVEMENT IN RESEARCH PROJECTS AND PROGRAMS

3/5/2017 - 31/7/2017: Research Project (no. 91875) with title: “Joint Postgraduate

Studies Programme “Informatics and Management””, Special

Account for Research Funds, AUTH.

Adjunct Lecturer (contracted) of the postgraduate course: “Databases

and Data mining” of the Department of Informatics, AUTH, for the

spring semester of 2017.

23/11/2016 - 28/2/2017: Research Project (no. 91877) with title: “Postgraduate Studies

Programme “Information and Communication Technologies””,

Special Account for Research Funds, AUTH.

Adjunct Lecturer (contracted) of the postgraduate course: “Spatial

and Multimedia Databases” of the Department of Informatics,

AUTH, for the fall semester of 2016.

8/4/2015 - 30/6/2015: Research Project (no. 21455) with title: “Services to connect

undergraduate and graduate students with the market”, Special

Account for Research Funds, AUTH.

Adjunct Lecturer (contracted) of the postgraduate course: “Advanced

Data Indexing” of the Department of Informatics, AUTH, for the

spring semester of 2015.

19/2/2015 - 30/6/2015: Research Project (no. 90410) with title: “15th

International

Conference on Web Information System Engineering (WISE

2014)”, Special Account for Research Funds, AUTH.

Assistant Editor and Internal Reviewer for the selection of papers

from the workshops of the conference WISE 2014, and their

publication in a post-proceedings volume by Springer.


International

Conference on Advanced Information Systems Engineering

(CAISE 2014)”, Special Account for Research Funds, AUTH.


from the proceedings of the conference CAISE 2014, and their

publication in a special issue of the Requirements Engineering

Journal by Springer.


International

Conference of Engineering Applications of Neural Networks

(EANN)”, Special Account for Research Funds, AUTH.


from the proceedings of the conference EANN, and their publication

in special issues of the scientific journals: Information Sciences and

Neurocomputing, by Elsevier.

2/4/2012 - 9/12/2012: Research Project 3Dlife: 3DLife is a network of excellence funded

by the European Union under THEME ICT-2009.1.5 “Networked

Media and 3D Internet” of the 7th

Framework Programme. 3DLife's

ultimate target is to lay the foundations of a European Competence

Centre under the name "Excellence in Media Computing &

Communication" or simply EMC2.

Researcher in 3DLife-EMC2 on a research project with title: “Multi-

Sort Indexing for Image Similarity Search”, in the area of Media

Computing & Communication and in cooperation with Information

Technologies Institute (ITI). After the successful completion of the

research, I received a scholarship and a fellowship diploma from

Queen Mary University of London.

1/1/2011 - 31/12/2012: Research Programme for the promotion of the exchange and

scientific cooperation between Greece and Germany (IKYDA

2011) with title: “Recommender Systems in Web2.0”.

Scientific cooperation between universities: (1) AUTH, and (2) Otto-

von-Guericke University, Magdemburg, Germany. The programme

was funded by the Greek State Scholarships Foundation (IKY).

Researcher – Member of the Greek research team. I designed and

implemented a recommendation system by combining social

networks’ data, social tags, user ratings and profiles.

26/1/2009 - 26/4/2013: Four-year European Research Project: FPS COST Action

FP0804, Forest Management Decision Support Systems

(FORSYS 2009-2013). The main objective of FORSYS was the

development of a European procedural framework, information

standards and guidelines, for the design, implementation, testing,

evaluation as well as the application of Decision Support Systems

(DSS) for forest management and multifunctional problems of

Forestry. In addition, to determine the requirements for the

application of DSS and to offer a consistent EU-wide quality

reference point for the development of DSS for forest management.

In this cost action, 24 countries participated along with Greece, with

national representatives, and 10 more institutions that do not belong

in the EU. It was funded by the European Commission, as part of the

EU RTD Framework Programme.

Researcher and active workgroup member in WG1: DSS architecture

and design, during the four years.

Moreover, I participated in almost all the meetings of the Working

Groups, which took place in various cities of the European Union.

4/12/2003 - 4/8/2004: Research Project with title: “Enhancing Computer Studies at the

Department of Applied Informatics, University of Macedonia of

Economic and Social Sciences”. The project was implemented

under the Operational Programme for Education and Initial

Vocational Training (O.P. “Education”). O.P. "Education" is one of

the Third Community Support Framework’s 24 Operational

Programmes (2000-2006) in Greece, and is co-financed by the

European Social Fund, the European Regional Development Fund

and national resources.

I worked as a programmer in this project (contracted), where:

a) I developed web applications and web databases that were hosted

on the website of University of Macedonia for the support of the

educational work and the promotion of the Postgraduate Studies

Programme.

b) I updated the website of University of Macedonia with educational

material from the various courses of the Postgraduate Studies

Programme of the Department of Applied Informatics of University

of Macedonia.

c) I checked, corrected and updated the lecture notes of the courses

“Design and Analysis of Algorithms” of the Undergraduate and the

Postgraduate Curriculum of the Department of Applied Informatics

of University of Macedonia (Instructor: Prof. K. Paparrizos).

1/11/2003 - 15/12/2003: Research Project “ITM” funded by the European Union in

collaboration with the Forest Research Institute of Thessaloniki

and the University of Vienna (BOKU).

Researcher and Programmer (contracted) on design and

implementation of a forest model management/simulator with 3D

graphics visualization capabilities using C++ and DirectX. I

developed a complete forest management simulation software

package entitled “DRYMOS” with the following main features: (i)

modeling and visualization of forest stands by using DirectX 3D

graphics, (ii) database management of forest stands data, (iii)

prediction and simulation of the evolution of the forest stands in

time, (iv) support of interactive tree plantings, tree thinning, snow

damages, regenerations into the stand, and various forestry scenarios.

The development of this software was made in the Forest Research

Institute of Thessaloniki and it was also presented at the National

Agricultural Research Foundation (N.AG.RE.F.).

PARTICIPATION IN CONFERENCES

International Conferences

o 2018 IEEE International Conference on INnovations in Intelligent SysTems and Applications

(INISTA), Thessaloniki, Greece, July 2018, (attendance).

o 21st International Conference on Theory and Practice of Digital Libraries (TPDL), Thessaloniki,

Greece, September 2017, (attendance).

o 16th

International Conference on Engineering Applications of Neural Networks (EANN),

Rhodes, Greece, September 2015, (session chair, attendance).

o 5th

International Conference on Model & Data Engineering (MEDI), Rhodes, Greece,

September 2015, (paper presentation, attendance).

o 15th

International Conference on Web Information System Engineering (WISE), Thessaloniki,

Greece, October 2014, (attendance).

o 20th

International Conference on Artificial Neural Networks and the collocated workshops

(ICANN), Thessaloniki, Greece, September 2010, (attendance).

o 5th

Conference on Artificial Intelligence Applications and Innovations and the collocated

workshops (AIAI), Thessaloniki, Greece, September 2009, (attendance).

o 10th

International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile

Systems (MSWiM), Chania, Greece, October 2007, (paper presentation, attendance).

o 10th

East-European Conference on Advances in Databases and Information Systems (ADBIS),

Thessaloniki, Greece, September 2006, (attendance).

National Conferences

o 14th

Panhellenic Conference on Informatics (PCI), Tripoli, Greece, September 2010, (paper

presentation, attendance).

o 5th

Hellenic Data Management Symposium (HDMS), Thessaloniki, Greece, September 2006,

(attendance).

PARTICIPATION IN COST ACTIONS, MEETINGS, WORKSHOPS

AND OTHER PROGRAMS

International Meetings

o 3rd cHiPSet Training School “Large Scale Data Mining and Machine Learning for Big Data

Analytics”, of the COST Action IC1406 (cHiPSet) “High-Performance Modeling and

Simulation for Big Data Applications”, Thessaloniki, Greece, September 2018, (member).

o Final Work Group and Management Committee Meeting for EU Cost Action FP0804, Forest

Management Decision Support Systems (FORSYS), and parallel conference: “Decision support

systems for Sustainable Forest Management”, Umeå, Sweden, April 2013, (workgroup

member).

o 2nd

Meeting of IKYDA Research Program, Magdeburg, Germany, December 2011, (member).

o 5th

Work Group and Management Committee Meeting, EU Cost Action FP0804, Forest

Management Decision Support Systems (FORSYS), Leuven, Belgium, November 2011,

(workgroup member).

o 4th


Management Decision Support Systems (FORSYS), Thessaloniki, Greece, June 2011,

(workgroup member).

o 3rd


Management Decision Support Systems (FORSYS), Brussels, Belgium, October 2010,

(workgroup member).

o 2nd


Management Decision Support Systems (FORSYS), Riga, Latvia, October 2009, (workgroup

member).

Workshops

o Educational Workshop with title: “3D Printing and Scanning - from theory to applications”,

Model-Experimental Senior High School of University of Macedonia, Thessaloniki, Greece,

January 2015, (member of the organizing committee, attendance).

o 3rd

Educational Workshop on New Technologies, Model-Experimental Senior High School of

University of Macedonia, Thessaloniki, Greece, December 2014, (member of the organizing

committee, educator, attendance):

I implemented the educational program: “Solving Geometry Problems with Geogebra”.

I participated also in the educational programs: “Edmodo: e-class”, “Interactive

presentations with Voicethread. On-line teaching through Web 2.0 tools”, “The design of a

simple web-page with Front Page”.

o Educational Workshop on Mathematics, 2nd

Model-Experimental Senior High School of

Thessaloniki, Greece, October 2014, (attendance).

o Educational Workshop with title: “Teaching of Mathematics, school necessities and university

involvement”, co-organized by the Department of Mathematics AUTH, Model-Experimental

Senior High-School of AUTH, and Model-Experimental Senior High-School of University of

Macedonia, Thessaloniki, Greece, 2014, (member of the organizing committee, attendance).

o 2nd

Educational Workshop on New Technologies, Model-Experimental Senior High School of



I implemented the educational program: “OCR-Tools for recognizing and reading general

and scientific documents”.

I participated also in the educational program: “Introduction to Hot Potatoes”.

o 1st Educational Workshop on New Technologies, Model-Experimental Senior High School of



I implemented the educational program: “Word processing with LaTeX”.

I participated also in the educational programs: “Web 2.0”, “Usage of interactive

whiteboards in the Natural Sciences and in Education in general”.

o 3rd

Student Conference on Informatics, Science Center and Technology Museum "NOESIS",

Thessaloniki, Greece, May 2011, (supervisor, paper presentation).

o Educational Workshop on Teaching of Mathematical Logic and Proof, Thessaloniki, Greece,

September 2010, (attendance).

o Scientific Conference on Innovation and Research in the Experimental School, University of

Macedonia, Thessaloniki, Greece, May 2010, (paper presentation, attendance).

Programs

o Internships Program Spring 2017, Department of Mathematics, Aristotle University,

Thessaloniki, Greece. I supported the internships program as a supervisor to student groups

(8/2/2017-7/4/2017).

o Internships Program Fall 2016, Department of Mathematics, Aristotle University,


(1/11/2016-31/12/2016).

o Internships Program Spring 2016, Department of Mathematics, Aristotle University,


(1/4/2016-31/5/2016).

o Educational Program “Youth Activ” within the Framework “Jean Monnet – Action KA1:

Information and Research Activities”, implemented by the University of Piraeus, Greece, March

2014, (workgroup member, attendance).

o Educational Program and Workshop with title: “Re-enforcing of the cultural potential of

students through formal, semi-formal and informal school practices”, Model-Experimental

Senior High School of University of Macedonia, Thessaloniki, Greece, March 2014, (member

of the organizing committee, workgroup member, attendance).

o Educational Program on New Technologies for the materialization of Projects and the formation

of teaching material, Model-Experimental Senior High School of University of Macedonia,

Thessaloniki, Greece, September 2013, (member of the organizing committee, attendance).

Invited Lectures - Talks

December 2013: Lecture with title: “Applications in Spatial Networks”, in the postgraduate

course: “Spatial Databases and GIS” (Fall Semester), Department of Informatics, AUTH.

May 1993: Research on theoretical models of Lebesque and on presentation of Peano space-

filling curves using computer graphics. Lecture with the title: “The space-filling curve of

Lebesque” in the Analysis Seminar in the Department of Mathematics, AUTH. (Archive of

Analysis Seminars 1992-2015, file manager: Prof. Dimitrios Betsakos).

February 1992: Research on algorithmic processing of theorems and examples from

Mathematical Analysis, and implementation of the studied algorithms, e.g. (a) general solution

of the polynomial equation of 3rd

degree, (b) solution of differential equations of 2nd

degree,

etc., Lecture for the results of this research in the Sector of Mathematical Analysis, Department

of Mathematics, AUTH.

March 1991: Research on developing computer graphics applications, which depict and

manage several types of mathematical functions (real, parametric, complex, multidimensional,

etc.) for educational and research purposes. Lecture for the results of this research in the Sector

of Mathematical Analysis, Department of Mathematics, AUTH.

PC-MEMBER

23rd International Database Engineering & Applications Symposium (IDEAS-2019)

9th International Conference on Web Intelligence, Mining and Semantics (WIMS-2019)

8th International Conference on Web Intelligence, Mining and Semantics (WIMS-2018)

REGULAR / EXTERNAL REVIEWER

in International Journals

The International Journal on Very Large Data Bases (VLDB) / Springer

Transactions on Knowledge and Data Engineering (TKDE) / IEEE

Data and Knowledge Engineering (DATAK) / Elsevier

Information Sciences (INS) / Elsevier

Big Data Research (BDR) / Elsevier

Distributed and Parallel Databases (DAPD) / Springer

Knowledge and Information Systems (KAIS) / Springer

International Journal of Data Science and Analytics (JDSA) / Springer

Transactions on Emerging Topics in Computing (TETC) / IEEE

Access / IEEE

Transactions on Neural Networks and Learning Systems (TNNLS) / IEEE

International Journal of Computer Systems Science and Engineering (IJCSSE) / CRL

Publishing

Engineering Intelligent Systems (EIS) / CRL Publishing

Journal of Computer Engineering and Information Technology (JCEIT) / SciTechnol

International Journal of Data Warehousing and Mining (IJDWM) / IGI Global

Information / MDPI

Informatics / MDPI

International Journal of Geo-Information (ISPRS) / MDPI

Symmetry / MDPI

Progress in Electromagnetic Research (PIER) / EMW Publishing

Journal of Electromagnetic Waves and Applications (JEMWA) / Taylor & Francis

Security and Communication Networks (SCN) / John Wiley & Sons, Ltd.

Software: Practice and Experience (SPE) / John Wiley & Sons, Ltd.

Complexity / John Wiley & Sons, Ltd.

International Journal of Security and Networks (IJSN) / Inderscience

International Journal of Advanced Intelligence Paradigms (IJAIP) / Inderscience

International Journal of High Performance Computing and Networking (IJHPCN) / Inderscience

Entropy / MDPI

Applied Sciences / MDPI

Mathematical and Computational Applications (MCA) / MDPI

Future Generation Computer Systems (FGCS) / Elsevier

Sensors / MDPI

Computer Science and Information Systems journal (ComSIS)

in International Conferences

International Conference on Data Engineering (ICDE)

International Conference on Extending Database Technology (EDBT)

International Conference on Knowledge Discovery and Data Mining (KDD)

International Conference on Advances in Geographic Information Systems (SIGSPATIAL-GIS)

International Symposium on Spatial and Temporal Databases (SSTD)

East-European Conference on Advances in Databases and Information Systems (ADBIS)

European Conference on Machine Learning and Principles and Practice of Knowledge

Discovery in Databases (ECML/PKDD)

International Conference on Database Systems for Advanced Applications (DASFAA)

International Conference on Statistical and Scientific Database Management (SSDBM)

International Conference on Recommender Systems (RECSYS)

International Conference on Web Information Systems Engineering (WISE)

International Conference on Web Intelligence, Mining and Semantics (WIMS)

International Conference on Artificial Neural Networks (ICANN)

International Conference on Mobile Data Management (MDM)

International Conference on Global Communications (GLOBECOM)

International Conference on Communications (ICC)

International Conference on Wireless Communications and Networking (WCNC)

International Conference on Connected Vehicles and Expo (ICCVE)

International Symposium on Programming and Systems (ISPS)

International Symposium on Intelligent Distributed Computing (IDC)

International Conference on Enterprise Information Systems (ICEIS)

International Joint conference on Software Technologies (ICSOFT)

International Conference on Mobile, Ubiquitous, and Intelligent Computing (MUSIC)

THESIS SUPERVISING

1. Thesis (in Greek): "Study and implementation of shortest path algorithms", Department of

Informatics, AUTH, Dimitra Papadimitriou, 2007.

2. Thesis (in Greek): "Search and study of methods for node labeling in large graphs", Department

of Informatics, AUTH, Thomas Kotios, 2010.

3. Postgraduate Thesis (in Greek): "Skyline query algorithms on streams of multidimensional

data", Department of Informatics, AUTH, Tzanakas Alexandros, 2016.

4. Postgraduate Thesis (in Greek): "Skyline query algorithms on large image databases",

Department of Informatics, AUTH, Georgiadis Nikolaos, 2016.

5. Postgraduate Thesis (in Greek): "Location-based trajectory similarity query algorithms in spatial

networks", Department of Informatics, AUTH, Pliakis Nikolaos, 2017.

TEACHING EXPERIENCE IN PUBLIC EDUCATION

Educator of Teachers of Secondary Education:

4/11/2009 - 16/11/2009: Educator of Teachers in Mathematics in the “Introductory Teacher

Training Program”, 3rd

Phase, 2nd

Regional Training Center of

Thessaloniki.

1/9/2008 - 10/9/2008: Educator of Teachers in Informatics in the project “Education and

Training of Teachers of Informatics”, part of the project “Training

Actions of Teachers of Informatics”, of the Operational Programme

“Information Society” of the 3rd

Community Support Framework

(CSF), 2nd

Educational Period, AUTH.

20/5/2008 - 31/5/2008: Educator of Teachers in Informatics in the project “Education and

Training of Teachers of Informatics”, part of the project “Training

Actions of Teachers of Informatics”, of the Operational Programme

“Information Society” of the 3rd

Community Support Framework

(CSF), 1st Educational Period, AUTH.

4/9/2007 - 13/9/2007: Educator of Teachers in Mathematics in the project «Intensive

Training Programs of Teachers of Secondary Education in the new

Teaching Packages”, organized by the Pedagogical Institute and the

Ministry of Education, and supported by the 3rd

Community Support

Framework (CSF) and the Operational Programme for Education and

Initial Vocational Training (O.P. “Education”), 2nd

Educational

Period, Regional Directory of Primary and Secondary Education of

Central Macedonia.

25/6/2007 - 27/6/2007: Educator of Teachers in Mathematics in the project «Intensive

Training Programs of Teachers of Secondary Education in the new

Teaching Packages”, organized by the Pedagogical Institute and the

Ministry of Education, and supported by the 3rd

Community Support

Framework (CSF) and the Operational Programme for Education and

Initial Vocational Training (O.P. “Education”), 1st Educational

Period, 2nd

Regional Training Center of Thessaloniki.

Organization of Educational Excellence Groups in the Secondary Education:

1. Organization of an Educational Excellence Group on “Astronomy” at the Model-Experimental

Senior High School of the University of Macedonia, and teaching in the school years: 2013-

2014, 2014-2015, 2015-2016, 2016-2017.

2. Organization of an Educational Excellence Group on “Web 2.0 Tools” at the Model-

Experimental Senior High School of the University of Macedonia, and teaching in the school

year 2012-2013.

Teacher of Secondary Education (permanent staff) of the Ministry of Education:

1. Teacher of Mathematics, Informatics and Astronomy in the Model-Experimental Senior High

School of the University of Macedonia, Thessaloniki, in the school years from 2009-2010 to

2016-2017.

2. Teacher of Mathematics, Informatics and Astronomy in the 1st Model-Experimental Senior

High School of Thessaloniki, in the school year 2008-2009.

3. Teacher of Mathematics in the High School of Meliki, Imathia, in the school year 2007-2008.

4. Teacher of Mathematics in the 2nd

Technical Vocational School of Alexandria and in the

High School of Trikala, Imathia, in the school year 2006-2007.


Technical Vocational School of Veria, Imathia, in the

school year 2005-2006.


Senior High School of Naousa, Imathia, in the school year

2004-2005.

Publications with Educational Content

Eleftherios Tiakas, Athanasiadis Ioannis, Ataloglou Vasileios, Toulikas Georgios, Tsingaras

Vyronas, “Drawing with Mathematical Equations”, 3rd

Student Conference on Informatics, 5

pages (in Greek), Science Center and Technology Museum “NOESIS”, Thessaloniki, May

2011.

Eleftherios Tiakas, “Simulating Trajectories of Solar System Objects and Phenomena in

Astronomy”, Conference on Innovation and Research at the Experimental School, 11 pages (in

Greek), University of Macedonia, Thessaloniki, May 2010.

2004-2005: I developed, as an innovation (because existing programs did not support certain

automation in designing and measuring geometric shapes and function graphs), specific

educational software to support teaching of chapters of Analysis and Geometry. This software

published on the web site www.e-yliko.gr (Educational Portal) of the Ministry of Education.

TEACHING EXPERIENCE IN PRIVATE EDUCATION

Teacher of Mathematics:

1993-2004: Teacher of Mathematics in Private Education Institutes and Private Schools.

a) Teaching Algebra, Analysis, Geometry, Analytic Geometry, Statistics to students attending

Primary, Lower Secondary and Upper Secondary Schools.

b) Teaching university courses to postgraduate and undergraduate students: Linear Algebra,

Analytic Geometry, Differential and Integral Calculus, Differential Equations, Linear

Programming, Number Theory, Applied Statistics.

Teacher of Informatics and Computer Science:

1. 1993-2003: Teacher of Computer Science and Informatics in the Private Education Institute

“Logica Computers”, to:

a) groups of postgraduate and undergraduate students,

b) groups of students attending Primary, Lower Secondary and Upper Secondary Schools,

c) special groups of professionals and individuals.

Courses taught:

o Primitive Systems and Programming Languages: Assembly language of Z80 and Motorola

6800 processors, and BASIC language of home micros: Texas Instruments TI99/4A, MSX-

Daewoo, Spectrum 16-48+, Amstrad 464-664-6128, Commodore 64-128, Amiga 500-1000.

o Accounting Commercial Software Packages: of Computer Logic, Singular and Unisoft

companies: “Horizons – General Accounting”, “Horizons – Commercial Management”,

“Warehouses and Sales Management”, “Mirage”, “Defacto”, “Personel”, and other packages

for accounting bookkeeping of B and C category.

o Programming Languages: Basic, Visual Basic, Visual Basic for Applications (VBA), Data

Access Objects (DAO), Fortran, Cobol, Pascal, Delphi, C, C++, Visual C++, SQL (Access-

SQL, SQL-Server, Oracle-SQL, MySQL), advanced graphics & sound programming,

Active-X Controls, Assembly 8088, 80x86 with MMX advanced graphics & sound

instructions, Direct-X Programming 2D-3D & advanced, OpenGL, HTML, XML, PHP,

JAVA Script, JAVA, Action Script, Prolog, Lisp, Clips, Strips, Object Oriented

Programming, UML.

o Operating Systems and Popular Software Packages: DOS, Windows, UNIX, LINUX, Word,

Excel, Access, Power Point, Data Base III-IV, Oracle, Page Maker, Corel Draw, Photoshop,

Internet Explorer, Outlook Express, Front Page, Wavelab, Sound Forge, Acid, Cubase, 3D

Studio, Vegas Video, Adobe Premier, Flash, AutoCAD, SPSS, MatLab, Mathematica.

o University Topics and Courses: Operating Systems, Databases, Networks, Principles of

Software Engineering, Software Design, Artificial Intelligence, Neural Networks,

Telematics and Internet, Informatics and Education, Discrete Mathematics, Analysis of

Algorithms, Data Structures, Digital Systems, Compilers, Grammars, Finite Automata,

Turing Machines.

2. December 1993: Teacher of Informatics in funded projects by the European Economic

Community (EEC). Teaching general use of computers and basic programming skills to special

groups of professionals and individuals.

COMPUTER PROGRAMMER/DEVELOPER IN COMPANIES (FREE-LANCER)

8/1/2000 – 31/8/2004:

1/9/2004 – 20/11/2012:

Computer Programmer/Developer in “TreeSoft” Software

Company, Alexandroupoli, Greece, which provides software

solutions and tools to Construction Companies, Contractors,

Engineers and Public Organizations, for more efficient management

of their files and archives.

I designed, developed and implemented business software

packages: ERP Systems, Logistics, Accounting Applications, and

several other specialized applications for: (a) Municipality

Management, (b) Lawyer Office Management, (c) Organization of

Activities, (d) Technical Works and Constructions Management, (e)

Public Works and Constructions Management, (f) Urban Buildings

Constructions Management.

I supported and upgraded the developed software packages whenever there was a requirement.

10/1/1998 - 21/12/2002: Computer Programmer/Developer in Jeronimo Groovy Radio

Station, Athens, Greece.

I designed, developed and implemented a specific management

application of the radio station for the compilation of its

broadcast program, which: (a) manages multimedia databases with

audio mp3 files and additional data, (b) recognizes and categorizes

the audio files in specific groups, (c) designs and constructs

automatically the playlist programs of the radio station for its

broadcast, based on several user-specific simple or complex criteria.

3/12/1993 - 31/8/2003: Computer Programmer/Developer in “Logica Computers”

business, Thessaloniki, Greece.

I designed, developed and implemented several specific software

packages to customers of the company, about:

o Warehouse and Products Management

o Customers and Suppliers Management

o Sales Management

o Accounting and Financial Applications

o Database Management

o Management of Multi-User Databases in Local Networks

o Music Editing Applications

o 3D Graphics and Animation Modeling Applications

o Encoding-Decoding and Cryptography Applications

o Educational Software

o Educational Games

Computer Service Technician in “Logica Computers” business,

Thessaloniki, Greece. During these ten years I experienced in a

wide variety of technical repairs in hardware, in software, in

maintenance of computer parts and peripherals, in system upgrades,

in computer assembling, as well as in installation of operating

systems, drivers and programs.

ADDITIONAL EDUCATION

2004 -2005: Introductory Teacher Training Program (1

st, 2

nd and 3

rd Phase), 1

st Regional

Training Center of Thessaloniki.

2003: ECDL-Advanced Diploma (Module 5 – Data Bases).

2003: ECDL Diploma (Windows, Word, Excel, Access, Power Point, Internet

Explorer, Outlook Express).

ADMINISTRATIVE RESPONSIBILITIES

1. 22/4/1996 - 31/8/2003: Managing Director of the company “Logica Computers”.

2. 3/4/2002 - 31/8/2004: Managing Member and Director of the Music-Record Company:

“Triangle Records Co.”.

MUSIC EDUCATION AND SKILLS

Music studies: classical piano lessons (7 years), music harmony, music creation, composition,

instrumentation, recording and production of music tracks.

Specialized knowledge in music creation, composition, instrumentation, recording and

production of music tracks using computer hardware & software applications and tools.

Specialized knowledge in: hardware & software analog and digital musical instruments,

synthesizers, samplers, sequencers, drum-machines, keyboards, sound editors, converters,

recorders, sound cards, effect machines, filters, compressors, amplifiers, and equalizers.

Specialized knowledge in programming of sound cards, and in music software development.

I composed over 100 completed music songs and tracks (instrumentations, productions,

remixes, remakes and new arrangements). Several of these songs and tracks were great radio

hits and published by the following record companies: FM-Records SA, Erial Records SA,

Warner Music SA, and Triangle Records (1996-2018).

Member of the Hellenic Society for the Protection of Intellectual Property (AEPI, 2002-2018).

HONORS - AWARDS - SCHOLARSHIPS

2012: Award from Queen Mary University of London for completing a 3DLife-EMC2

fellowship with a research project in the area of Media Computing & Communication.

2006: Award and Scholarship from the State Scholarships Foundation - IKY due to excellent

performance during undergraduate studies in the academic year 2005-2006 at the Department of

Informatics, AUTH.



Mathematics, AUTH.



Mathematics, AUTH.



Mathematics, AUTH.

1991: Award and Scholarship from the Department of Meteorology and Climatology of

AUTH for the construction of a flexible computer application for the management and the

processing of meteorological data and forecasting models.

1990: Candidate member of the 2nd

International Olympiad in Informatics, Minsk, Belorussian

Republic, Soviet Union (IOI’90).

1990: Award due to excellent performance in the 2nd

National Competition of Informatics

organized by Greek Computer Society, Athens, Greece.

1990: Candidate member of the 31st International Olympiad in Mathematics, Beijing, China.

1989: Silver Medal in the 6th

National Olympiad in Mathematics organized by the Hellenic

Mathematical Society, Athens, Greece.

1989: Award due to excellent performance in the 49th

National Competition in Mathematics

organized by the Hellenic Mathematical Society, Greece.


National Olympiad in Mathematics

organized by the Hellenic Mathematical Society, Athens, Greece.




1988: Award for participation in the 1st Balkan Summer School for talented young students in

Mathematics, organized by the Hellenic Mathematical Society, Ioannina, Greece.

1987: Bronze Medal in the 4th

National Olympiad in Mathematics organized by the Hellenic

Mathematical Society, Athens, Greece.




1986: Award due to excellent performance in the 3rd

National Olympiad in Mathematics

organized by the Hellenic Mathematical Society, Athens, Greece.




1986-1990: Publish of my specialized solutions to several problems of Olympiads in

Mathematics and Mathematical Competitions, in specific issues of the journals: “Euclid” and

“Dimension” of the Hellenic Mathematical Society, Athens.

Citations Table*

Top Publication Year Number of citations

Journal Articles 1 J2 2009 78

2 J8 2014 35

3 J4 2011 26

4 J6 2013 25

5 J3 2009 10

6 J7 2013 6

7 J10 2015 4

8 J5 2013 4

9 J11 2016 3

10 J12 2016 2

11 J9 2014 1

Conference Papers 1 C6 2010 100

2 C8 2011 77

3 C1 2006 45

4 C10 2014 16

5 C11 2014 8

6 C4 2010 7

7 C13 2015 4

8 C3 2008 4

9 C7 2011 2

10 C2 2007 2

11 C15 2016 1

12 C12 2015 1

13 C5 2010 1

Book Chapters 1 CH1 2012 3

Technical Reports 1 TR1 2016 2

Total number of Citations: 467 * The numbers are based on the results from Google Scholar as recorded on 31 January 2019.

Links

Partial list of citations from Google Scholar.

Partial list of publications from the Data Engineering Lab, Department of Informatics, Aristotle

University of Thessaloniki, Greece.

Partial list of publications from DBLP.

Partial list of citations from Microsoft Academic Search.

Partial list of publications from DBLife.

Partial list of publications from the Collection of Computer Science Bibliographies.

http://scholar.google.gr/citations?user=VY10EioAAAAJ&hl=el&oi=sra

http://delab.csd.auth.gr/pubs.php?member=tiakas

http://delab.csd.auth.gr/pubs.php?member=tiakas

http://www.informatik.uni-trier.de/~ley/pers/hd/t/Tiakas:Eleftherios.html

http://academic.research.microsoft.com/Author/3572024/eleftherios-tiakas

http://dblife.cs.wisc.edu/person/Eleftherios_Tiakas&query=tiakas

http://liinwww.ira.uka.de/csbib?query=%2Bau:TiakasE*+%2Bau:Tiakas&maxnum=200&sort=year

Publication Analysis

Journal Articles

J1. Eleftherios Tiakas, Stefanos Ougiaroglou, Petros Nicopolitidis. "Efficient algorithms for

constructing broadcast disks programs in asymmetric communication environments",

Telecommunication Systems (Springer), vol. 41, no. 3, pp. 185-209, May 2009.

A well-known technique for broadcast program construction is the Broadcast Disks technique.

However, in the Broadcast Disks approach there are some important disadvantages. For

example some parts of the broadcast program remain empty during the construction procedure

and the disk relative frequencies have to be selected very carefully. This paper gives a new

approach of the broadcast program construction in a Broadcast Disk System, presenting three

new algorithms, which face successfully these problems. According to this approach, the

broadcast program is constructed with the minimum possible length, while retaining the selected

disk relative frequencies and keeps the average delays on retrieving data-items low. The

constructed broadcast programs have no empty parts, and retain their desired properties in any

numbered combination of disk relative frequencies. We implemented all methods in a simulator

application and experimental results show that our approach is more efficient than Broadcast

Disks in all cases.

J2. Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos, Dragan Stojanovic, Slobodanka Djordjevic-Kajan. "Searching for similar

trajectories in spatial networks", Journal of System and Software (Elsevier), vol. 82, no. 5,

pp. 772-788, May 2009.

In several applications, data objects move on pre-defined spatial networks such as road

segments, railways, and invisible air routes. Many of these objects exhibit similarity with

respect to their traversed paths, and therefore two objects can be correlated based on their

motion similarity. Useful information can be retrieved from these correlations and this

knowledge can be used to define similarity classes. In this paper, we study similarity search for

moving object trajectories in spatial networks. The problem poses some important challenges,

since it is quite different from the case where objects are allowed to move freely in any direction

without motion restrictions. New similarity measures should be employed to express similarity

between two trajectories that do not necessarily share any common sub-path. We define new

similarity measures based on spatial and temporal characteristics of trajectories, such that the

notion of similarity in space and time is well expressed, and moreover they satisfy the metric

properties. In addition, we demonstrate that similarity range queries in trajectories are efficiently

supported by utilizing metric-based access methods, such as M-trees.

J3. Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos. "Node and edge selectivity estimation for range queries in spatial

networks", Information Systems (Elsevier), vol. 34, no. 3, pp. 328-352, May 2009.

Modern applications requiring spatial network processing pose several interesting query

optimization challenges. Spatial networks are usually represented as graphs, and therefore,

queries involving a spatial network can be executed by using the corresponding graph

representation. This means that the cost for executing a query is determined by graph properties

such as the graph order and size (i.e., number of nodes and edges) and other graph parameters.

In this paper, we present novel methods to estimate the number of nodes and edges in regions of

interest in spatial networks, towards predicting the space and time requirements for range

queries. The methods are evaluated by using real-life and synthetic data sets. Experimental

results show that the number of nodes and edges can be estimated efficiently and accurately,

with relatively small space requirements, thus providing useful information to the query

optimizer.

J4. Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Progressive

processing of subspace dominating queries", The VLDB Journal (Springer), vol. 20, no. 6,

pp. 921-948, December 2011.

A top-k dominating query reports the k items with the highest domination score. Algorithms for

efficient processing of this query have been recently proposed in the literature. Those methods,

either index based or index free, apply a series of pruning criteria toward efficient processing.

However, they are characterized by several limitations, such as (1) they lack progressiveness

(they report the k best items at the end of the processing), (2) they require a multi-dimensional

index or they build a grid-based index on-the-fly, which suffers from performance degradation,

especially in high dimensionalities, and (3) they do not support vertically decomposed data. In

this paper, we design efficient algorithms that can handle any subset of the dimensions in a

progressive manner. Among the studied algorithms, the Differential Algorithm shows the best

overall performance.

J5. Panagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos. "A unified framework

for link and rating prediction in multi-modal social networks", International Journal of

Social Network Mining (Inderscience), vol. 1, no. 3/4, pp. 225-253, January 2013.

Multi-modal Social Networks (MSNs) allow users to form explicit (by adding new friends in

their network) or implicit (by similarly co-rating items) social networks. Previous research work

was limited either to the prediction of new relationships among users (i.e. Link Prediction

problem) or to the prediction of item ratings (i.e. Rating Prediction problem and Item

Recommendations). Recent link prediction methods infer future relationships among users, by

also exploiting information from their implicit networks (i.e. user-item rating network). On the

other hand, Rating Prediction methods predict the user’s rating behavior on items, by also

exploiting information from their explicit network (i.e. friendship network). In this paper, we

develop a framework to incorporate both research directions into a unified model. We extend

our Social-Union algorithm, which initially focused on the rating prediction problem, in order to

be applied also on the link prediction problem. Social-Union combines similarity matrices

derived from heterogeneous (unipartite and bipartite) explicit or implicit MSNs. Moreover, we

propose an effective weighting strategy of MSNs influence based on their structured density.

We also generalize our model for combining multiple social networks.We perform an extensive

experimental comparison of the proposed method against existing link and rating prediction

algorithms, using synthetic and two real data sets (Epinions and Flixter). Our experimental

results show that our Social-Union framework is more effective in both rating and link

prediction.

J6. Eleftherios Tiakas, Dimitrios Rafailidis, Anastasios Dimou, Petros Daras. "MSIDX: Multi-

Sort Indexing for Efficient Content-Based Image Search and Retrieval", Transactions on

Multimedia (IEEE), vol. 15, no. 6, pp. 1415-1430, October 2013.

In this paper, a novel approximate indexing scheme for efficient content-based image search and

retrieval is presented, called Multi-Sort Indexing (MSIDX). The proposed scheme analyzes high

dimensional image descriptor vectors, by employing the value cardinalities of their dimensions.

The dimensions' value cardinalities, an inherent characteristic of descriptor vectors, are the

number of discrete values in the dimensions. As expected, value cardinalities significantly vary,

due to the existence of several extraction methods. Moreover, different quantization and

normalization techniques used in the extraction process, have a strong impact on the dimensions'

value cardinalities. Since dimensions with high value cardinalities have more discriminative

power, a multiple sort algorithm is used to reorder the descriptors' dimensions according to their

value cardinalities, in order to increase the probability of two similar images to lie within a close

constant range. The expected bounds of the constant range are defined in detail, following

deterministic and probabilistic analyses. The proposed scheme is fully suitable (a) for real-time

indexing of images, and (b) for searching and retrieving relevant images with an efficient query

processing algorithm. In our experiments with five real datasets, we show the superiority of the

proposed approach against hashing methods, also suitable for approximate similarity search.

J7. Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "On Estimating the

Maximum Domination Value and the Skyline Cardinality of Multi-Dimensional Data

Sets", International Journal of Knowledge-Based Organizations (IGI Global), vol. 3, no. 4,

pp. 61-83, October 2013.

The last years there is an increasing interest for query processing techniques that take into

consideration the dominance relationship between items to select the most promising ones,

based on user preferences. Skyline and top-k dominating queries are examples of such

techniques. A skyline query computes the items that are not dominated, whereas a top-k

dominating query returns the k items with the highest domination score. To enable query

optimization, it is important to estimate the expected number of skyline items as well as the

maximum domination value of an item. In this article, we provide an estimation for the

maximum domination value under the distinct values and attribute independence assumptions.

We provide three different methodologies for estimating and calculating the maximum

domination value and we test their performance and accuracy. Among the proposed estimation

methods, our method Estimation with Roots outperforms all others and returns the most accurate

results. We also introduce the eliminating dimension, i.e., the dimension beyond which all

domination values become zero, and we provide an efficient estimation of that dimension.

Moreover, we provide an accurate estimation of the skyline cardinality of a data set.

J8. Panagiotis Symeonidis, Eleftherios Tiakas. "Transitive node similarity: predicting and

recommending links in signed social networks", World Wide Web Journal (Springer), vol.

17, no. 4, pp. 743-776, July 2014.

Online social networks (OSNs) like Facebook, Myspace, and Hi5 have become popular,

because they allow users to easily share content. OSNs recommend new friends to registered

users based on local features of the graph (i.e., based on the number of common friends that two

users share). However, OSNs do not exploit the whole structure of the network. Instead, they

consider only pathways of maximum length 2 between a user and his candidate friends. On the

other hand, there are global approaches, which detect the overall path structure in a network,

being computationally prohibitive for huge-size social networks. In this paper, we define a basic

node similarity measure that captures effectively local graph features (i.e., by measuring

proximity between nodes). We exploit global graph features (i.e., by weighting paths that

connect two nodes) introducing transitive node similarity. We also derive variants of our

method that apply to different types of networks (directed/undirected and signed/unsigned). We

perform extensive experimental comparison of the proposed method against existing

recommendation algorithms using synthetic and real data sets (Facebook, Hi5 and Epinions).

Our experimental results show that our FriendTNS algorithm outperforms other approaches in

terms of accuracy and it is also time efficient. Finally, we show that a significant accuracy

improvement can be gained by using information about both positive and negative edges.

J9. Nantia Iakovidou, Eleftherios Tiakas, Konstantinos Tsichlas, Yannis Manolopoulos.

"Going over the three dimensional protein structure similarity problem", Artificial

Intelligence Review (Springer), vol. 42, no. 3, pp. 445-459, October 2014.

This article presents in detail our novel proposed methodology for detecting similarity between

or among three dimensional protein structures. The innovation of our algorithm relies on the

fact that during the similarity process, it has the ability to combine many attributes together and

fulfil lots of preconditions, which are extensively discussed throughout the paper. Our concept

is also supported by an efficient and effective indexing scheme, that provides convincing results

comparing to other known methods.

J10. Zaigham Faraz Siddiqui, Eleftherios Tiakas, Panagiotis Symeonidis, Myra

Spiliopoulou, Yannis Manolopoulos. "Learning Relational User Profiles and

Recommending Items as Their Preferences Change", International Journal on Artificial

Intelligence Tools (World Scientific Publishing Company), vol. 24, no. 2, 31 pages, April

2015.

Over the last decade a vast number of businesses have developed online e-shops in the web.

These online stores are supported by sophisticated systems that manage the products and record

the activity of customers. There exist many research works that strive to answer the question

“what items are the customers going to like” given their historical profiles. However, most of

these works do not take into account the time dimension and cannot respond efficiently when

data are huge. In this paper, we study the problem of recommendations in the context of multi-

relational stream mining. Our algorithm “xStreams” first separates customers based on their

historical data into clusters. It then employs collaborative filtering (CF) to recommend new

items to the customers based on their group similarity. To evaluate the working of xStreams, we

use a multi-relational data generator for streams. We evaluate xStreams on real and synthetic

datasets.

J11. Eleftherios Tiakas, George Valkanas, Apostolos N. Papadopoulos, Yannis

Manolopoulos, Dimitrios Gunopulos. "Processing Top-k Dominating Queries in Metric

Spaces", Transactions on Database Systems (ACM), vol. 40, no. 4, 38 pages, article 23,

January 2016.

Top-k dominating queries combine the natural idea of selecting the k best items with a

comprehensive “goodness” criterion based on dominance. A point p1 dominates p2 if p1 is as

good as p2 in all attributes and is strictly better in at least one. Existing works address the

problem in settings where data objects are multidimensional points. However, there are domains

where we only have access to the distance between two objects. In cases like these, attributes

reflect distances from a set of input objects and are dynamically generated as the input objects

change. Consequently, prior works from the literature can not be applied, despite the fact that

the dominance relation is still meaningful and valid. For this reason, in this work, we present the

first study for processing top-k dominating queries over distance-based dynamic attribute

vectors, defined over a metric space. We propose four progressive algorithms that utilize the

properties of the underlying metric space to efficiently solve the problem, and present an

extensive, comparative evaluation on both synthetic and real-world data sets.

J12. Dimitris Zianis, Gavriil Spyroglou, Eleftherios Tiakas, Kalliopi Radoglou. "Bayesian

and classical models to predict aboveground tree biomass allometry", Forest Science

Journal, vol. 62, no. 3, pp. 247-259, June 2016.

Total dry aboveground tree biomass (M) allometric equations were derived from 25

destructively sampled Hungarian oak (Quercus frainetto Ten.) trees, growing in Chalkidiki

peninsula (Northern Greece). The regression models were developed under Bayesian and

classical statistical approaches. All approaches captured equally well the variability in the

recorded M values across the diameter (D) range of the sampled trees. The Informative

Bayesian (IB) approach based on prior distributions about the allometric parameters and the size

dependent error variance provided quite accurate M predictions. Linear Regression (LR),

Nonlinear Regression (NLR) and Non-informative Bayesian (NB) approaches failed to predict

M distribution when validation was performed against an independent dataset previously

collected from the study area. It was concluded that adaptation of Bayesian theorem in tree

allometry research is strongly supported. A published simplified Bayesian approach, based on

six-tree sample, was applied in our dataset and is found to be a promising tool for allometric

relationships. Further research is needed in order to robustly support or reject such an approach.

Theoretical values of the slope in M-D allometry were validated against the derived parameter.

A number of scaling parameters may quite accurately describe tree biomass allometry, rather

than a unique pair of them.

Papers in Conference Proceedings

C1. Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos, Dragan Stojanovic, Slobodanka Djordjevic-Kajan. "Trajectory Similarity

Search in Spatial Networks", Proceedings of the 10th International Database Engineering

& Applications Symposium (IEEE / IDEAS), pp. 185-192, Delhi, India, December 2006.

In several applications, data objects are assumed to move on predefined spatial networks such as

road segments, railways, invisible air routes. Moving objects may exhibit similarity with respect

to their traversed paths, and therefore two objects can be correlated based on their path

similarity. In this paper, we study similarity search for moving object trajectories for spatial

networks. The problem poses some important challenges, since it is quite different from the case

where objects are allowed to move without any motion restrictions. Experimental results

performed on real-life spatial networks show that trajectory similarity can be supported in an

effective and efficient manner by using metric-based access methods.

C2. Eletherios Tiakas, Stefanos Ougiaroglou, Petros Nicopolitidis. "Efficient broadcast disks

program construction in asymmetric communication environments", Proceedings of the

10th International Symposium on Modelling, Analysis and Simulation of Wireless and

Mobile Systems (ACM / MSWiM), pp. 279-283, Chania, Crete Island, Greece, October

2007.

A well-known technique for broadcast program construction is the Broadcast Disks. However, it

has important disadvantages, as for example that the broadcast program construction procedure

leaves some parts of the broadcast program empty. This paper proposes a new approach for the

construction of the broadcast program. Specifically, it presents three new algorithms, which face

the problems of the Broadcast Disk Technique. According to our approach, the broadcast

program is constructed with the minimum possible length, respecting the selected disk relative

frequencies and keeps the average delays of retrieving data-items low. The constructed

broadcast programs have no empty parts and retain their desired properties in any combination

of disk relative frequencies. Experimental results show that this approach is more efficient than

Broadcast Disks in all cases.

C3. Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis

Manolopoulos. "Selectivity estimation in spatial networks", Proceedings of the 23rd

Annual Symposium on Applied Computing (ACM / SAC), pp. 852-856, Fortaleza, Ceara,

Brazil, March 2008.

Modern applications requiring spatial network processing pose many interesting query

optimization challenges. In many cases, query processing depends on the corresponding graph

size (number of nodes and edges) and other graph parameters. This dependency may be local or

global. In this paper, we present novel methods to estimate the number of nodes in regions of

interest in spatial networks, towards predicting the space and time requirements of range

queries. We examine all methods by using real-life and synthetic spatial networks. Experimental

results show that the number of nodes can be estimated efficiently and accurately with small

space requirements, thus providing useful information to the query optimizer.

C4. Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Graph Node

Clustering via Transitive Node Similarity", Proceedings of the 14th Panhellenic

Conference on Informatics (IEEE / PCI), pp. 72-77, Tripoli, Greece, September 2010.

This paper studies the problem of cluster detection in undirected graphs by using transitive node

similarity methods. Well-defined semi-metric measures are proposed to compute the similarity

between the nodes of the graph, and the clustering is based on the resulted similarity values. The

proposed algorithm has three major steps. In the first step, which is optional, a ranking of all the

nodes of the graph is performed by using application specific criteria (if any). In the second

step, a specific node is selected and the similarity values from this node to all other nodes are

computed and maintained into a similarity list. In the third step, from the resulted similarity list

values, the first cluster is constructed from the nodes that have a sufficient similarity score. The

last two steps, are repeated, until all the nodes of the graph have been clustered. This

methodology was tested in real-world data sets and provides promising clustering results. The

results of a representative real-word case of clustering nodes in a real road network are

presented and validated both numerically and visually.

C5. Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Estimation of the

Maximum Domination Value in Multi-dimensional Data Sets", Proceedings of the 14th

East-European Conference on Advances in Databases and Information Systems (Springer /

ADBIS), pp. 505-519, Novi Sad, Serbia, September 2010.

The last years there is an increasing interest for query processing techniques that take into

consideration the dominance relationship between objects to select the most promising ones,

based on user preferences. Skyline and top-k dominating queries are examples of such

techniques. A skyline query computes the objects that are not dominated, whereas a top-k

dominating query returns the k objects with the highest domination score. To enable query

optimization, it is important to estimate the expected number of skyline objects as well as the

maximum domination value of an object. In this paper, we provide an estimation for the

maximum domination value for data sets with statistical independence between their attributes.

We provide three different methodologies for estimating and calculating the maximum

domination value, and we test their performance and accuracy. Among the proposed estimation

methods, our method Estimation with Roots outperforms all others and returns the most accurate

results.

C6. Panagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos. "Transitive node

similarity for link prediction in social networks with positive and negative links",

Proceedings of the 4th ACM Conference on Recommender Systems (ACM / RECSYS), pp.

183-190, Barcelona, Spain, September 2010.

Online social networks (OSNs) like Facebook, and Myspace recommend new friends to

registered users based on local features of the graph (i.e. based on the number of common

friends that two users share). However, OSNs do not exploit the whole structure of the network.

Instead, they consider only pathways of maximum length 2 between a user and his candidate

friends. On the other hand, there are global approaches, which detect the overall path structure

in a network, being computationally prohibitive for huge-size social networks. In this paper, we

define a basic node similarity measure that captures effectively local graph features. We also

exploit global graph features introducing transitive node similarity. Moreover, we derive

variants of our method that apply in signed networks. We perform extensive experimental

comparison of the proposed method against existing recommendation algorithms using synthetic

and real data sets (Facebook, Hi5 and Epinions). Our experimental results show that our

FriendTNS algorithm outperforms other approaches in terms of accuracy and it is also time

efficient. We show that a significant accuracy improvement can be gained by using information

about both positive and negative edges.

C7. Zaigham Faraz Siddiqui, Myra Spiliopoulou, Panagiotis Symeonidis, Eleftherios Tiakas.

"A Data Generator for Multi-Stream Data", Proceedings of the 2nd International

Workshop on Mining Ubiquitous and Social Environments (Springer / MUSE), pp. 63-70,

Athens, Greece, September 2011.

We present a stream data generator. The generator is mainly intended for multiple interrelated

streams, in particular for objects with temporal properties, which are fed by dependent streams.

Such data are e.g. customers their transactions: learning a model of the customers requires

considering the stream of their transactions. However, the generator can also be used for

conventional stream data, e.g. for learning the concepts of the transaction stream only. The

generator is appropriate for testing classification and clustering algorithms on concept discovery

and adaptation to concept drift. The number of concepts in the data can be specified as

parameter to the generator; the same holds for the membership of an instance to a class. Hence,

it is also appropriate for synthetic datasets on overlapping classes or clusters.

C8. Panagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos. "Product

recommendation and rating prediction based on multi-modal social networks",

Proceedings of the 5th ACM Conference on Recommender Systems (ACM / RECSYS), pp.

61-68, Chicago, IL, USA, October 2011.

Online Social Rating Networks (SRNs) such as Epinions and Flixter, allow users to form

several implicit social networks, through their daily interactions like co-commenting on the

same products, or similarly co-rating products. The majority of earlier work in Rating Prediction

and Recommendation of products (e.g. Collaborative Filtering) mainly takes into account

ratings of users on products. However, in SRNs users can also built their explicit social network

by adding each other as friends. In this paper, we propose Social-Union, a method which

combines similarity matrices derived from heterogeneous (unipartite and bipartite) explicit or

implicit SRNs. Moreover, we propose an effective weighting strategy of SRNs influence based

on their structured density. We also generalize our model for combining multiple social

networks. We perform an extensive experimental comparison of the proposed method against

existing rating prediction and product recommendation algorithms, using synthetic and two real

data sets (Epinions and Flixter). Our experimental results show that our Social-Union algorithm

is more effective in predicting rating and recommending products in SRNs.

C9. Nantia Iakovidou, Eleftherios Tiakas, Konstantinos Tsichlas: "DISCO: A New Algorithm

for Detecting 3D Protein Structure Similarity", Proceedings of the Artificial Intelligence

Applications and Innovations Workshops (Springer / AIAI), pp. 622-631, Halkidiki, Greece,

September 2012.

Protein structure similarity is one of the most important aims pursued by bioinformatics and

structural biology, nowadays. Although quite a few similarity methods have been proposed

lately, yet fresh algorithms that fulfill new preconditions are needed to serve this purpose. In

this paper, we provide a new similarity measure for 3D protein structures that detects not only

similar structures but also similar substructures to a query protein, supporting both multiple and

pairwise comparison procedures and combining many comparison characteristics. In order to

handle similarity queries we utilize efficient and effective indexing techniques such as M-trees

and we provide interesting results using real, previously tested protein data sets.

C10. Eleftherios Tiakas, George Valkanas, Apostolos N. Papadopoulos, Yannis

Manolopoulos, Dimitrios Gunopulos: "Metric-Based Top-k Dominating Queries",

Proceedings of the 17th International Conference on Extending Database Technology

(Open Proceedings / EDBT), pp. 415-426, Athens, Greece, March 2014.

Top-k dominating queries combine the natural idea of selecting the k best items with a

comprehensive “goodness” criterion based on dominance. A point p1 dominates p2 if p1 is as

good as p2 in all attributes and is strictly better in at least one. Existing works address the

problem in settings where data objects are multidimensional points. However, there are domains

where we only have access to the distance between two objects. In cases like these, attributes

reflect distances from a set of input objects and are dynamically generated as the input objects

change. Consequently, prior works from the literature cannot be applied, despite the fact that the

dominance relation is still meaningful and valid. For this reason, in this work, we present the

first study for processing top-k dominating queries over distance-based dynamic attribute

vectors, defined over a metric space. We propose four progressive algorithms that utilize the

properties of the underlying metric space to efficiently solve the problem, and present an

extensive, comparative evaluation on both synthetic and real world data sets.

C11. Zaigham Faraz Siddiqui, Eleftherios Tiakas, Panagiotis Symeonidis, Myra

Spiliopoulou, Yannis Manolopoulos. "xStreams: Recommending Items to Users with

Time-evolving Preferences", Proceedings of the 4th International Conference on Web

Intelligence, Mining and Semantics (ACM / WIMS), Article 22, 12 pages, Thessaloniki,

Greece, June 2014.

Over the last decade a vast number of businesses have developed online e-shops in the web.

These online stores are supported by sophisticated systems that manage the products and record

the activity of customers. There exist many research works that strive to answer the question

"what items are the customers going to like" given their historic profiles. However, most of

these works miss to take into account the time dimension and cannot respond efficiently when

data are huge. In this paper, we study the problem of recommendations in the context of multi-

relational stream mining. Our algorithm first separates customers based on their historic data

into clusters. It then employs collaborative filtering (CF) to recommend new items to the

customers based on their clustering structure. We evaluate our algorithm on two data sets,

MovieLens and a synthetic data set.

C12. Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Top-k

Dominating Queries: a Survey (invited)", Proceedings of the 17th International

Symposium on Programming and Systems (ISPS), 10 pages, Algiers, Algeria, April 2015.

Top-k dominating queries combine the advantages of top-k queries and skyline queries, and

eliminate their disadvantages. They return k objects with the highest domination score, which is

defined as the number of dominated objects. As a top-k query, the user can bound the number

of returned results through the parameter k, and like a skyline query a user-selected scoring

function is not required. Top-k dominating queries have been studied by different perspectives,

such as in indexed and nonindexed multi-dimensional data using efficient exact computation

algorithms, in uncertain data using randomized algorithms with accuracy guarantees, and in

data streams. In addition, top-k dominating queries have been studied over distance-based

dynamic attribute vectors, defined over a metric space, using efficient progressive algorithms.

Top-k dominating queries have become an important tool for decision support, data mining,

web search, and multi-criteria retrieval applications.

C13. Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis Manolopoulos. "Skyline

Queries: an Introduction (invited)", Proceedings of the 6th International Conference on

Information, Intelligence, Systems & Applications (IISA), 6 pages, Corfu, Greece, July

2015.

During the two past decades, skyline queries were used in several multi-criteria decision

support applications. Given a dominance relationship in a dataset, a skyline query returns the

objects that cannot be dominated by any other objects. Skyline queries were studied extensively

in multidimensional spaces, in subspaces, in metric spaces, in dynamic spaces, in streaming

environments, and in time-series data. Several algorithms were proposed for skyline query

processing, such as window-based, progressive, distributed, geometric-based, index-based,

divide-and-conquer, and dynamic programming algorithms. Moreover, several variations were

proposed to solve application-specific problems like k-dominant skylines, top-k dominating

queries, spatial skyline queries, and others. As the number of objects that are returned in a

skyline query may become large, there is also an extensive study for the cardinality of skyline

queries. This extensive research depicts the importance of skyline queries and their variations

in modern applications.

C14. Eleftherios Tiakas, Dimitrios Rafailidis. "Scalable Trajectory Similarity Search Based

on Locations in Spatial Networks", Proceedings of the 5th International Conference on

Model and Data Engineering (Springer / MEDI), LNCS vol. 9344, pp. 213-224, Rhodes,

Greece, September 2015.

In this paper, we propose an efficient query processing algorithm that returns the trajectory

results in low search time. We limit the calculation of pairwise shortest path distances between

the set of query locations and the spatial nodes, by highly reducing the preprocessing

requirements. Also, we introduce a spatiotemporal similarity measure, based on which the

temporal-to-spatial significance of the trajectory results can be easily modified and the query

locations can be spatially prioritized according to users’ preferences. In our experiments with a

real-world road network, we show that the proposed method has approximately ten times less

preprocessing requirements than the competitive methods and reduces the search time by two

orders of magnitude at least.

C15. Alexander Tzanakas, Eleftherios Tiakas, Yannis Manolopoulos. "Skyline Algorithms

on Streams of Multidimensional Data", Proceedings of the 20th East-European Conference

on Advances in Databases and Information Systems (Springer / ADBIS), pp. 63-71, Prague,

Czech Republic, August 2016.

We compare three algorithms for skyline processing on streams of multidimensional data with

centralized processing, namely, the Look-Out, Lazy and Eager methods, with different dataset

types and dimensionalities, data cardinalities and sliding window sizes. Experimental results

for time performance and memory consumption are presented. In addition, the problem of

computing the exclusive dominance region in higher dimensions is reviewed and a novel

correct solution is proposed.

C16. Nikolaos Georgiadis, Eleftherios Tiakas, Yannis Manolopoulos. "Detecting Intrinsic

Dissimilarities in Large Image Databases through Skylines", Proceedings of the 9th

International Conference on Management of Digital EcoSystems (ACM / MEDES), pp.

194-201, Bangkok, Thailand, November 2017, [Best Paper Award].

In this paper we try to detect dissimilar images in image databases without defining a similarity

ranking function by capturing the intrinsic dissimilarities of image descriptor vectors. To this

end, we apply the skyline operation using their multi-dimensional descriptor vectors. We

implemented a number of skyline methods, combined with four hashing state-of-the-art

algorithms for data partitioning to create efficient indexing to secondary memory. We

compared and evaluated their results by using two real image datasets to measure the

performance and the effectiveness of the implemented algorithms. Detailed results show the

efficiency and effectiveness of our approach.

C17. Theodoros Tzouramanis, Eleftherios Tiakas, Apostolos N. Papadopoulos, Yannis

Manolopoulos. "The Range Skyline Query", Proceedings of the 27th International

Conference on Information and Knowledge Management (ACM / CIKM), pp. 47-56,

Torino, Italy, October 2018.

The range skyline query retrieves the dynamic skyline for every individual query point in a

range by generalizing the point-based dynamic skyline query. Its wide-ranging applications

enable users to submit their preferences within an interval of 'ideally sought' values across

every dimension, instead of being limited to submit their preference in relation to a single

sought value. This paper considers the query as a hyper-rectangle iso-oriented towards the axes

of the multi-dimensional space and proposes: (i) main-memory algorithmic strategies, which

are simple to implement and (ii) secondary-memory pruning mechanisms for processing range

skyline queries efficiently. The proposed approach is progressive and I/O optimal. A

performance evaluation of the proposed technique demonstrates its robustness and

practicability.

Book Chapters

CH1. Theodoros Semertzidis, Dimitrios Rafailidis, Eleftherios Tiakas, Michael G. Strintzis,

Petros Daras. "Multimedia Indexing, Search and Retrieval in Large Databases of Social

Networks", Social Media Retrieval, Computer Communications and Networks series

(Springer), pp. 43-63, 2012.

Social networks are changing the way multimedia content is shared on the Web, by allowing

users to upload their photos, videos, and audio content, produced by any means of digital

recorders such as mobile/smart-phones and Web/digital cameras. This plethora of content

created the need for finding the desired media in the social media universe. Moreover, the

diversity of the available content inspired users to demand and formulate more complicated

queries. In the social media era, multimedia content search is promoted to a fundamental feature

toward efficient search inside social multimedia streams, content classification, context and

event based indexing. In this chapter, an overview of multimedia indexing and searching

algorithms, following the data growth curve, is presented in detail. This chapter is thematically

structured in two parts. In the first part, pure multimedia content retrieval issues are presented,

while in the second part, the social aspects and new, interesting views on multimedia retrieval in

the large social media databases are discussed.

CH2. Gavriil Spyroglou, Eleftherios Tiakas, Gregor Chatziphilippidis, Vasiliki Kazana.

"The design and use of forest decision support systems in Greece", Computer-based tools

for supporting forest management. The experience and the expertise world-wide (Epsilon

Open Archive), pp. 152-167, 2014.

This paper presents the design and use of forest decision support systems in Greece. The

decision support systems were classified according to the methods and models that used for

their training, what technical knowledge management was used and what methods, if any, were

used for the contribution of participants and stakeholders. The decision support systems were

classified also as to the time horizon of their application: Long-term or strategic interest with a

horizon of 25 years, medium or regular interest with a horizon of 5-10 years, and short or

business interest with a horizon from one day to one year. Finally they were split between those

that take into account the spatial resolution and those who do not. In Greece there are 12

different forest decision support systems but which are personal efforts of researchers that

created them through several research programs. There is no clear Greek forest policy regarding

the use of such systems at headquarters and operational level.

Technical Reports

TR1. Alexander Tzanakas, Eleftherios Tiakas, Yannis Manolopoulos. "Revisited skyline

query algorithms on streams of multidimensional data", Technical Report, Aristotle

University of Thessaloniki, 2016.

This paper focuses on the analysis and evaluation of skyline query algorithms on streams of

multidimensional data. It presents three algorithms and evaluates them with different types of

datasets, number of dimensions and "Sliding Window" sizes. The results of these experiments

are reviewed according to time performance, memory consumption and the size of the skyline.

TR2. Nikolaos Pliakis, Eleftherios Tiakas, Yannis Manolopoulos. "Efficient Progressive

Processing of Trajectories on Road Networks", Technical Report, Aristotle University of

Thessaloniki, 2018.

The demand for efficient retrieval and query processing pertaining to trajectories in spatially

constrained networks (e.g., road networks, rivers/ports vessel monitoring, etc.) has caused an

increased research interest in the past decade, in both industry and academia. In this work, we

target the problem of efficient progressive evaluation of trajectories and we present a novel

methodology based on a variant of Cluster extended Adjacency List (CeAL). We also

investigate the applicability of the state-of-the-art access methods to efficiently retrieve

trajectories in spatial networks. Specifically, we examine FNR-trees [17] and MON-trees [11]

against our variation of the Cluster-extended Adjacency Lists (CeAL), which has been

designed for application in location-based trajectory similarity top-k queries, where the user

defines locations and time restrictions [40]. In addition: (1) we extend all the above access

methods to efficiently handle trajectories of objects that move through very large spatial

networks; and (2) to enhance their performance, we create an entirely new implementation

framework to generate trajectories and to test the trajectory retrieval for each approach. We

conducted extensive experimental evaluations which demonstrate that the comparisons between

R-tree-based methods are clearly in favour of MON-trees. Complementary to this, though, the

comparisons between R-tree-based methods and the proposed CeAL method show that the

latter structure prevails overall in space and time complexity. We also identify some open

issues that could further advance the present findings.

TR3. Nikolaos Georgiadis, Eleftherios Tiakas, Yannis Manolopoulos, Apostolos N.

Papadopoulos. "Skyline-based Dissimilarity of Images", Technical Report, Aristotle

University of Thessaloniki, 2019.

In this paper, we aim at capturing the intrinsic dissimilarities of image descriptors in large

image collections, i.e., to detect dissimilar (i.e., diverse) images without defining an explicit

similarity or distance function. To this end, we adopt skyline query processing techniques for

large image databases, based on their high-dimensional descriptor vectors. The novelty of the

proposed methodology lies in the use of skyline techniques empowered by state-of-the-art

hashing schemes to enable effective data partitioning and indexing in secondary memory,

towards supporting large image databases. The proposed approach is evaluated experimentally

by using three real-world image datasets. Performance evaluation results demonstrate that

images lying on the skyline have largely different characteristics, which depend on the type of

the descriptor. Thus, these skyline items can be used as seeds to apply clustering in large image

databases. In addition, we observe that skyline processing using hash-based indexing structures

is significantly faster than index-free skyline computation and also more efficient than skyline

computation with hierarchical indexing structures. Based on our results, the proposed approach

is both efficient (regarding runtime) and effective (with respect to image diversity) and

therefore can be used as a base for more complex data mining tasks such as clustering.

Documents

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