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Extracting Relevant Attribute Values for Improved Search
September/October 2007 (vol. 11 no. 5)
pp. 26-35
Sonia Bergamaschi, University of Modena and Reggio Emili
Claudio Sartori, University of Bologna
Francesco Guerra, University of Modena and Reggio Emili
Mirko Orsini, University of Modena and Reggio Emili
A new kind of metadata offers a synthesized view of an attribute's values for a user to exploit when creating or refining a search query in data-integration systems. The extraction technique that obtains these values is automatic and independent of an attribute domain but parameterized with various metrics for similarity measures. The authors describe a fully implemented prototype and some experimental results to show the effectiveness of "relevant values" when searching a knowledge base.
Index Terms:
knowledge and data engineering tools and techniques, clustering, classification, association rules, metadata, semantic knowledge management
Citation:
Sonia Bergamaschi, Claudio Sartori, Francesco Guerra, Mirko Orsini, "Extracting Relevant Attribute Values for Improved Search," IEEE Internet Computing, vol. 11, no. 5, pp. 26-35, Sept.-Oct. 2007, doi:10.1109/MIC.2007.105
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