Capturing the semiotic relationship between terms

Authors: Hargood, C., Millard, D. and Weal, M.

Journal: New Review of Hypermedia and Multimedia

Volume: 16

Publisher: Taylor and Francis

DOI: 10.1080/13614568.2010.499571

Tags describing objects on the web are often treated as facts about a resource, whereas it is quite possible that they represent more subjective observations. Existing methods of term expansion expand terms based on dictionary definitions or statistical information on term occurrence. Here we propose the use of a thematic model for term expansion based on semiotic relationships between terms; this has been shown to improve a system's thematic understanding of content and tags and to tease out the more subjective implications of those tags. Such a system relies on a thematic model that must be made by hand. In this article, we explore a method to capture a semiotic understanding of particular terms using a rule-based guide to authoring a thematic model. Experimentation shows that it is possible to capture valid definitions that can be used for semiotic term expansion but that the guide itself may not be sufficient to support this on a large scale. We argue that whilst the formation of super definitions will mitigate some of these problems, the development of an authoring support tool may be necessary to solve others.

This source preferred by Charlie Hargood

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Authors: Hargood, C., Millard, D.E. and Weal, M.J.

Journal: New Review of Hypermedia and Multimedia

Volume: 16

Issue: 1-2

Pages: 71-84

eISSN: 1740-7842

ISSN: 1361-4568

DOI: 10.1080/13614568.2010.499571

Tags describing objects on the web are often treated as facts about a resource, whereas it is quite possible that they represent more subjective observations. Existing methods of term expansion expand terms based on dictionary definitions or statistical information on term occurrence. Here we propose the use of a thematic model for term expansion based on semiotic relationships between terms; this has been shown to improve a system's thematic understanding of content and tags and to tease out the more subjective implications of those tags. Such a system relies on a thematic model that must be made by hand. In this article, we explore a method to capture a semiotic understanding of particular terms using a rule-based guide to authoring a thematic model. Experimentation shows that it is possible to capture valid definitions that can be used for semiotic term expansion but that the guide itself may not be sufficient to support this on a large scale. We argue that whilst the formation of super definitions will mitigate some of these problems, the development of an authoring support tool may be necessary to solve others. © 2010 Taylor & Francis.

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