Exploiting tag similarities to discover synonyms and homonyms in folksonomies. (14th August 2012)

• Record Type: Journal Article
• Authors: Eynard, Davide; Mazzola, Luca; Dattolo, Antonina
• Other Names: Di lorio Angelo guestEditor.; Rossi Davide guestEditor.; Zacchiroli Stefano guestEditor.
• Is Part Of: Software, practice & experience. Volume 43:Number 12(2013)
• Page Start: 1437
• Page End: 1457
• Publication Date: 2012-08-14
• Subjects: folksonomies -- tag clustering -- tag disambiguation -- tag similarity; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2150
• Languages: English
• ISSNs: 0038-0644

Abstract

SUMMARY: Tag‐based systems are widely available, thanks to their intrinsic advantages, such as self‐organization, currency, and ease of use. Although they represent a precious source of semantic metadata, their utility is still limited. The inherent lexical ambiguities of tags strongly affect the extraction of structured knowledge and the quality of tag‐based recommendation systems. In this paper, we propose a methodology for the analysis of tag‐based systems, addressing tag synonymy and homonymy at the same time in a holistic approach: in more detail, we exploit a tripartite graph to reduce the problem of synonyms and homonyms; we apply a customized version of Tag Context Similarity to detect them, overcoming the limitations of current similarity metrics; finally, we propose the application of an overlapping clustering algorithm to detect contexts and homonymies, then evaluate its performances, and introduce a methodology for the interpretation of its results. Copyright © 2012 John Wiley & Sons, Ltd.