Sitthisarn, S, Lau, LMS and Dew, PM (2011) Semantic keyword search for expert witness discovery. In: 2011 International Conference on Semantic Technology and Information Retrieval (STAIR). STAIR'11: International Conference on Semantic Technology and Information Retrieval, 28 Jun 2011 - 29 Jun 2011, Kuala Lumpur, Malaysia. IEEE , 18 - 25 . ISBN 978-1-61284-354-4
In the last few years, there has been an increase in the amount of information stored in semantically enriched knowledge bases, represented in RDF format. These improve the accuracy of search results when the queries are semantically formal. However framing such queries is inappropriate for inexperience users because they require specialist knowledge of ontology and syntax. In this paper, we explore an approach that automates the process of converting a conventional keyword search into a semantically formal query in order to find an expert on a semantically enriched knowledge base. A case study on expert witness discovery for the resolution of a legal dispute is chosen as the domain of interest and a system named SKengine is implemented to illustrate the approach. As well as providing an easy user interface, our experiment shows that SKengine can retrieve expert witness information with higher precision and higher recall, compared with the other system, with the same interface, implemented by a vector model approach.
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|Institution:||The University of Leeds|
|Academic Units:||The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)|
|Depositing User:||Symplectic Publications|
|Date Deposited:||26 Aug 2011 13:09|
|Last Modified:||16 Sep 2016 14:06|