A Network Model Approach to Retrieval in the Semantic Web

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Author(s): Peter Scheir (Graz University of Technology and Know-Center Graz, Austria), Stefanie N. Lindstaedt (Know-Center Graz and Graz University of Technology,Austria)and Chiara Ghidini (Fondazione Bruno Kessler, Italy)
Copyright: 2008
Volume: 4
Issue: 4
Pages: 29
Source title: International Journal on Semantic Web and Information Systems (IJSWIS)
Editor(s)-in-Chief: Brij Gupta (Asia University, Taichung City, Taiwan)
DOI: 10.4018/jswis.2008100103

Keywords: Computer Science & IT / Information Science Reference / Semantic Web / Web Technologies

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Abstract

While it is agreed that semantic enrichment of resources would lead to better search results, at present the low coverage of resources on the Web with semantic information presents a major hurdle in realizing the vision of search on the Semantic Web. To address this problem, we investigate how to improve retrieval performance in settings where resources are sparsely annotated with semantic information. Techniques from soft computing are employed to find relevant material that was not originally annotated with the concepts used in a query. We present an associative retrieval model for the Semantic Web and evaluate if and to what extent the use of associative retrieval techniques increases retrieval performance. The evaluation of new retrieval paradigms, such as retrieval based on technology for the Semantic Web, presents an additional challenge since no off-the-shelf test corpora exist. Hence, we give a detailed description of the approach taken to evaluate the information retrieval service we have built.

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A Network Model Approach to Retrieval in the Semantic Web

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