Abstract
Search is seen as a key application that can benefit from semantic technology with improvements to recall and precision over conventional Information Retrieval techniques. This paper describes Squirrel, a search and browse tool that provides access to semantically annotated data. Squirrel provides combined keyword based and semantic searching. The intention is to provide a balance between the speed and ease of use of simple free text search and the power of semantic search. In addition, the ontological approach provides the user with a much richer browsing experience. Squirrel builds on and integrates a number of semantic technology components. These include machine learning and information extraction components which generate, extract and manage semantic metadata contained within and about textual documents at index time. A number of run-time components have also been integrated to deliver an enhanced user experience which goes beyond merely presenting a list of documents as a query response. The tool has been trialled and evaluated in two case studies and we report early results from this exercise, revealing promising results.
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Duke, A., Glover, T., Davies, J. (2007). Squirrel: An Advanced Semantic Search and Browse Facility. In: Franconi, E., Kifer, M., May, W. (eds) The Semantic Web: Research and Applications. ESWC 2007. Lecture Notes in Computer Science, vol 4519. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72667-8_25
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DOI: https://doi.org/10.1007/978-3-540-72667-8_25
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