JIST 2012

Utilizing Linked Open Data (LOD) Resources for

Semantic Enhancement of User-Generated Content

Dong-Po Deng1,2, Guan-Shuo Mai3, Cheng-Hsin Hsu3, Chin-Lung Chang1,4, Tyng-Ruey Chuang1, and Kwang-Tsao Shao3

1ITC, University of Twente, Enschede, the Netherlands

2Institute of Information Science & 3Biodiversity Research Center,Academia Sinica, Taipei, Taiwan

4Department of Computer Science and Information EngineeringNational Taiwan University of Science and Technology

Taipei, Taiwan

Thursday, February 7, 2013

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Outline

BackgroundMotivationData CollectionLOD resources - LODE and LOD TGNAn approach for processing UGC Information Extraction Information Formalization Information Reuse

Conclusion remarking

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Background

Web 2.0 technologies enable people to contribute their content on the web, e.g. wiki, blog, tagging

Social media utilize web 2.0 technologies to support social interactive on the web, e.g. twitter, flickr, facebook

The content on the web (or/and social media) contributed by people is called “User-Generated Content” (UGC)

UGC is mainly multimedia or textual dataUGC is considered as a potential resource for scientific projects, e.g. citizen science

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Background(cont.)

There are several problems to harvest UGC to scientific purposes The unstructured UGC is difficult to handle The semantics of UGC is often ambiguous or/and poor Social media is not designed for scientific purposes

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Courtesy from http://www.datenform.de/mapeng.html


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Motivation

LOD datasets as resources LOD aims on how to make data available on the Web, and to interconnect data with the aim of increasing its value for users

about 300 datasets consisting of over 31 billion RDF triples within LOD projects.

Each entry representing a fact in LOD datasets has a Unique Resource Identifier (URI) which is referenceable and linkable on the Web.

The high interconnectivity between entries potentially increases discoverability, reusability, and the utility of information

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Motivation (cont.)

Therefore, if named entities of UGC can be identified and connected to entries of LOD, the semantics of named entities would be disambiguated, so that the UGC could be easier to process.

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Data collection

Two Facebook interest groups for ecological observations in Taiwan

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http://www.facebook.com/groups/roadkilled/ http://www.facebook.com/groups/enjoymoths/


http://www.facebook.com/groups/roadkilled/

http://www.facebook.com/groups/roadkilled/

http://www.facebook.com/groups/enjoymoths/

http://www.facebook.com/groups/enjoymoths/

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Ecological Observations on Facebook

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LOD Ecology

Linked Open Data of Ecology (LODE) is a validated dataset from a LOD project.

LODE integrated 5 previously distributed databases:

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TFRI: Taiwan Forestry Research Institute


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LODE in Linked Open Data Cloud

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LODE in Linked Open Data Cloud

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LOD Taiwan Geographic Name (TGN)

LOD TGN is mainly transferred from Taiwan Gazetteer via LOD principles

LOD TGN has 159,241 geographic name entries, in which 17,442 entries are linked to geonames.org

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Outline



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Information Extraction Information Reuse

Information Formalization

An approach for processing UGC

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Outline



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Problems in Chinese species names in Facebook ecological observations

玉帶鳳蝶 (Papilio Polytes)

曙鳳蝶 (Atrophaneura Horishana)

琉璃紋鳳蝶 (Papilio Hermosanus)

曙鳳

玉帶

琉璃Adjective Noun

細紋 (pronounced Si-Wen, meaning “fine veined”

細紋新蠍蛉細紋蠍蛉細紋黃鉤蛾

...15 species names with prefix name “細紋”

(1)

(2)

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Confidence value =

Identifying shortened species names

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Determine a species name for a thread

What if several species names had mentioned in one thread? We used three criteria How many Like does the post or the comments get?

How prestigious are the people who post or make comments?

How many times does a species name occur in a thread?

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The problems of geographic names in Facebook ecological observations

特生中心

特有生物研究保育中心Te-You-Sheng-Wu-Yan-Jiou-Bao-Yu-Jhong-Sin

An example:The Endemic Species Research Institute

Te-Sheng-Jhong-Sin

is shorten to

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The problems of geographic names in Facebook ecological observations

特生中心

特有生物研究保育中心Te-You-Sheng-Wu-Yan-Jiou-Bao-Yu-Jhong-Sin

An example:The Endemic Species Research Institute

Te-Sheng-Jhong-Sin

is shorten to

There are no rules to shorten long geographic names

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Identifying shortened geographic names

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The ontology...

is relied on a Facebook thread, which is an entity comprised of social media contents involving peoples, places, time periods, photos, and links to other contents

uses standard vocabularies, Semantically-Interlinked Online communities (SIOC) can be used to represent the structure of Facebook posts, comments, and threads.

Friend of a Friend (FOAF) can be used to describe content creators,

and Dublin Core for the interlinked contents they created

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An ontology for formalizing the extractedinformation from Facebook threads

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http://140.109.28.64:2020/page/thread/177883715557195_440860179259546

Transfer ecological observations in Facebook to RDF

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http://140.109.28.64:2020/page/thread/177883715557195_438916509453913

http://140.109.28.64:2020/page/thread/177883715557195_438916509453913

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http://140.109.28.64:2020/page/thread/177883715557195_440860179259546

Transfer ecological observations in Facebook to RDF

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http://140.109.28.64:2020/page/thread/177883715557195_438916509453913

http://140.109.28.64:2020/page/thread/177883715557195_438916509453913

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The extracted species name from the Facebook thread is linked to LOD resources

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A taxon of Theretra Nessus is the extracted species name

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A taxon of Theretra Nessus is the extracted species name

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This entry is connected to LODE via owl:sameAs


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The extracted place name from the Facebook thread is linked to LOD resources

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The entry of LOD TGN transferred from Taiwan Gazetteer

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The entry of LOD TGN transferred from Taiwan Gazetteer

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It is linked to geonames.org via owl:sameAs


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Publish the processed Facebook ecological observations

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A semantic annotation plug-in for entering geographic names in Facebook posts

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This study reports our experiences in transferring FB ecological observations to interlink to LOD resources (LODE and LOD TGN)

With these information extraction tools and LOD resources, we developed a tool for semantic enhancement of user input.

The LOD TGN is an ongoing project. In the future, we will consolidate the feature types of the geographic names, and we plan to make the LOD TGN a geospatial semantics reference resource.

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Thank you for your attentions

Questions?

[email protected]

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JIST 2012