Ernesto William De Luca, Alan Said, Matthias Böhmer and Florian Michahelles

Ernesto William De Luca, Alan Said, Matthias Böhmer and Florian Michahelles

Organizers

Ernesto William De Luca

Technische Universität Berlin. DAI-Labor Head of the Competence Center

for Information Retrieval and Machine Learning. (http://www.dai-labor.de/en/irml)

E-mail: [email protected]

13.02.2011 2 Context-Awareness in Retrieval and Recommendation (CARR2011)

Organizers

Alan Said

Technische Universität Berlin. DAI-Labor Member of the Competence

Center for Information Retrieval and Machine Learning. (http://www.dai-labor.de/en/irml)



Organizers

Matthias Böhmer

German Research Center for AI DFKI Researcher at Innovative Retail

Laboratory(http://www.innovative-retail.de)



Organizers

Florian Michahelles

Auto-ID Labs at ETH Zurich Zurich, Switzerland Associate director

(http://www.im.ethz.ch/people/fmichahelles)



Aim of the CaRR Workshop

Invite the community to a discussion in which we will try to find new creative ways to handle context-awareness

Improve the exchange of ideas between different communities involved (user interfaces, machine learning, information retrieval and recommendation)

13.02.2011 Context-Awareness in Retrieval and Recommendation (CARR2011)

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Previous Workshops

Context-awareness in Retrieval and Recommendation

Current SOA systems are generally context-ignorant, CAMRa focused on identifying and utilizing contextual data in real-life data from Moviepilot and Filmtipset.

13.02.2011 7

www.filmtipset.se

www.moviepilot.com

Context-Awareness in Retrieval and Recommendation (CARR2011)

Challenge on Context-aware Movie Recommendation (CAMRa2010)joint event with the Workshop on Context-aware

Recommender Systems (CARS-2010)in conjunction with the ACM Recommender Systems

2010 Conference (RecSys2010).

http://www.dai-labor.de/camra2010/

Can We Define Context?

”Any information that can be used to characterise the situation of entities”, Dey 2001

1.Item context• Seasonal (Christmas, Oscar’s)• Relation (movie sequel, director, actor)

2.User context• Surroundings (weather, location)• Company (alone, with friends)• Mood/emotions• any user related factor


+•Filters relevant information•Ad hoc recommendations•Aware of changes

-•What is context?•Where do we find it?

Why do we need Context?


Context-aware information

It is widely available in various ways interaction patterns, location, devices,

annotations, query suggestions and user profiles

It is becoming more and more important for enhancement of retrieval performance and

recommendation results personalization and adaptation of information


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CaRR general information

16 Submissions - 9 Accepted (6 Long, 3 Short) 56% Acceptance Rate

Every submission was evaluated by at least three of the 36 Members of the program committee.

Proceedings wil be published in ACM DL

All related information are available at:

http://www.dai-labor.de/carr2011/


CaRR Topics

CaRR Papers cover different topics:

Information Retrieval Recommender Systems Natural Language Processing and

Recommender Systems Smart Environments


Agenda (1/6)

Session 1 (9:00-10:30)9:00 – 9:15 Context-awareness in Retrieval and RecommendationErnesto William De Luca; Alan Said; Matthias Böhmer; Florian Michahelles

9:15 – 9:45 Towards a Context-Sensitive Online NewspaperJeremy Jancsary; Friedrich Neubarth; Stephanie Schreitter; Harald Trost


Agenda (2/6)

Session 1 (9:00-10:30)9:45- 10:00 (short) Implicit Acquisition of Context for Personalization of Information Retrieval SystemsChang Liu; Nicholas J. Belkin

10:00-10:30 (instead of 16:00 – 16:30) Guidance and Support for Healthy Food Preparation in an Augmented KitchenJurgen Wagner; Gijs Geleijnse; Aart van Halteren

Break (10:30-11:00)


Agenda (3/6)

Session 2 (11:00-13:00)11:00-12:00 Innovative Retail Laboratory: Assistive Technology in Retail Environments.Antonio Krüger (Invited Keynote)

12:00-12:30 Real-time, Location-aware Collaborative Filtering of Web ContentThomas Sandholm; Hang Ung

12:30-13:00 RecLab: A System For eCommerce Recommender Research with Real Data, Context and FeedbackDarren Vengroff

Lunch (13:00-14:00)


Agenda (4/6)

Session 3 (14:00-15:30)14:00-14:15 (short) Cross-lingual Recommender System for Research PapersKiyoko Uchiyama; Akiko Aizawa; Hidetsugu Nanba; Takeshi Sagara

14:15-14:30 (short) Utilizing Implicit Feedback and Context to Recommend Mobile Applications from First UseChristoffer Davidsson; Simon Moritz


Agenda (5/6)

Session 3 (14:00-15:30)14:30-15:00 Context-Aware POI Recommendations in an Automotive Scenario using Multi-Criteria Decision Making MethodsRoland Bader; Eugen Neufeld; Wolfgang Woerndl; Vivian Prinz

15:00-15:30 Designing Activity-aware Recommender Systems for Operating Rooms, Afsaneh Doryab; Jakob E. Bardram

Break (15:30-16:00)


Agenda (6/6)

Session 4 (16:00-17:30)16:00 - 17:30 Open Discussion trying to focus on the CARR problems and questions.


Thanks!


Agenda (Session 1)

Session 1 (9:00-10:30)9:15 – 9:45 Towards a Context-Sensitive Online NewspaperJeremy Jancsary; Friedrich Neubarth; Stephanie Schreitter; Harald Trost9:45- 10:00 (short) Implicit Acquisition of Context for Personalization of Information Retrieval SystemsChang Liu; Nicholas J. Belkin10:00-10:30 (instead of 16:00 – 16:30) Guidance and Support for Healthy Food Preparation in an Augmented KitchenJurgen Wagner; Gijs Geleijnse; Aart van Halteren

Break (10:30-11:00)


Agenda (Session 2)

Session 2 (11:00-13:00)11:00-12:00 Innovative Retail Laboratory: Assistive Technology in Retail Environments.Antonio Krüger (Invited Keynote)12:00-12:30 Real-time, Location-aware Collaborative Filtering of Web ContentThomas Sandholm; Hang Ung12:30-13:00 RecLab: A System For eCommerce Recommender Research with Real Data, Context and FeedbackDarren Vengroff

Lunch (13:00-14:00)


Agenda (Session 3)Session 3 (14:00-15:30)14:00-14:15 (short) Cross-lingual Recommender System for Research PapersKiyoko Uchiyama; Akiko Aizawa; Hidetsugu Nanba; Takeshi Sagara14:15-14:30 (short) Utilizing Implicit Feedback and Context to Recommend Mobile Applications from First UseChristoffer Davidsson; Simon Moritz14:30-15:00 Context-Aware POI Recommendations in an Automotive Scenario using Multi-Criteria Decision Making MethodsRoland Bader; Eugen Neufeld; Wolfgang Woerndl; Vivian Prinz15:00-15:30 Designing Activity-aware Recommender Systems for Operating Rooms, Afsaneh Doryab; Jakob E. Bardram

Break (15:30-16:00)


Agenda (Session 4)

Session 4 (16:00-17:30)16:00 - 17:30 Open Discussion trying to focus on the CARR problems and questions.


Agenda (Session 4) CARR problems and questions:

What is context? Is context-awareness

in retrieval and recommendation necessary? Which benefits come from

context-aware retrieval and recommendation systems? How do user interfaces handle context? In what ways can context improve HCI? How can we combine

general- and user-centric context-aware technologies? How should context affect the way

information is presented?13.02.2011 24 Context-Awareness in Retrieval and

Recommendation (CARR2011)

CARR Topics Context-aware information retrieval Context-aware profiling, clustering and collaborative

filtering Machine learning for context-aware information retrieval

and ontology learning Ubiquitous and context-aware computing Use of context-aware technologies in UI/HCI Context-aware advertising Recommendations for mobile users Context-awareness in portable devices


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Agenda (Session 4)

Documents

Ernesto William De Luca, Alan Said, Matthias Böhmer and Florian Michahelles