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.
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. © 2007 IEEE.
Extracting Relevant Attribute Values for Improved Search / Bergamaschi, Sonia; Guerra, Francesco; Orsini, Mirko; C., Sartori. - In: IEEE INTERNET COMPUTING. - ISSN 1089-7801. - STAMPA. - 11:5(2007), pp. 26-35. [10.1109/MIC.2007.105]
Extracting Relevant Attribute Values for Improved Search
BERGAMASCHI, Sonia;GUERRA, Francesco;ORSINI, Mirko;
2007
Abstract
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. © 2007 IEEE.
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