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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
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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