Augmenting Lightweight Domain Ontologies with Social Evidence Sources

Albert Weichselbraun, Gerhard Wohlgenannt, Arno Scharl

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

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.
Original languageEnglish
Title of host publication9th International Workshop on Web Semantics, 21st International Workshop on Database and Expert Systems Application (DEXA 2020)
Editors Tjoa, A. Min and Wagner, Roland R.
Place of PublicationBilbao, Spain
PublisherIEEE Computer Society Press
Pages771 - 776
Publication statusPublished - 2010

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