Quotation Weichselbraun, Albert and Wohlgenannt, Gerhard and Scharl, Arno. 2010. Augmenting Lightweight Domain Ontologies with Social Evidence Sources. In 9th International Workshop on Web Semantics, 21st International Workshop on Database and Expert Systems Application (DEXA 2020), Hrsg. Tjoa, A. Min and Wagner, Roland R. 771-776. Bilbao, Spain: IEEE Computer Society Press.


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Abstract

Recent research shows the potential of utilizing data collected through Web 2.0 applications to capture changes in a domain's terminology. This paper presents an approach to augment corpus-based ontology learning by considering terms from collaborative tagging systems, social networking platforms, and micro-blogging services. The proposed framework collects information on the domain's terminology from domain documents and a seed ontology in a triple store. Data from social sources such as Delicious, Flickr, Technorati and Twitter provide an outside view of the domain and help incorporate external knowledge into the ontology learning process. The neural network technique of spreading activation is used to identify relevant new concepts, and to determine their positions in the extended ontology. Evaluating the method with two measures (PMI and expert judgements) demonstrates the significant benefits of social evidence sources for ontology learning.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title Augmenting Lightweight Domain Ontologies with Social Evidence Sources
Title of whole publication 9th International Workshop on Web Semantics, 21st International Workshop on Database and Expert Systems Application (DEXA 2020)
Editor Tjoa, A. Min and Wagner, Roland R.
Page from 771
Page to 776
Location Bilbao, Spain
Publisher IEEE Computer Society Press
Year 2010

Associations

People
Weichselbraun, Albert (Former researcher)
Wohlgenannt, Gerhard (Former researcher)
Scharl, Arno (Former researcher)
Organization
Institute for Data, Process and Knowledge Management (AE Polleres) (Details)
Institute for Information Systems and Society IN (Details)
Research Institute for Computational Methods FI (Details)
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