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Semantic Search on Unstructured Data: Explicit Knowledge through Data Recycling

Semantic Search on Unstructured Data: Explicit Knowledge through Data Recycling

Alex Kohn, François Bry, Alexander Manta
Copyright: © 2010 |Volume: 6 |Issue: 2 |Pages: 19
ISSN: 1552-6283|EISSN: 1552-6291|EISBN13: 9781609603953|DOI: 10.4018/jswis.2010040102
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MLA

Kohn, Alex, et al. "Semantic Search on Unstructured Data: Explicit Knowledge through Data Recycling." IJSWIS vol.6, no.2 2010: pp.17-35. http://doi.org/10.4018/jswis.2010040102

APA

Kohn, A., Bry, F., & Manta, A. (2010). Semantic Search on Unstructured Data: Explicit Knowledge through Data Recycling. International Journal on Semantic Web and Information Systems (IJSWIS), 6(2), 17-35. http://doi.org/10.4018/jswis.2010040102

Chicago

Kohn, Alex, François Bry, and Alexander Manta. "Semantic Search on Unstructured Data: Explicit Knowledge through Data Recycling," International Journal on Semantic Web and Information Systems (IJSWIS) 6, no.2: 17-35. http://doi.org/10.4018/jswis.2010040102

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Abstract

Studies agree that searchers are often not satisfied with the performance of current enterprise search engines. As a consequence, more scientists worldwide are actively investigating new avenues for searching to improve retrieval performance. This paper contributes to YASA (Your Adaptive Search Agent), a fully implemented and thoroughly evaluated ontology-based information retrieval system for the enterprise. A salient particularity of YASA is that large parts of the ontology are automatically filled with facts by recycling and transforming existing data. YASA offers context-based personalization, faceted navigation, as well as semantic search capabilities. YASA has been deployed and evaluated in the pharmaceutical research department of Roche, Penzberg, and results show that already semantically simple ontologies suffice to considerably improve search performance.

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