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.
Sonia Bergamaschi, Francesco Guerra, Mirko Orsini, Claudio Sartori (2007). Extracting relevant attribute values for improved search. IEEE INTERNET COMPUTING, 11, 5, 16-25 [10.1109/MIC.2007.105].
Extracting relevant attribute values for improved search
SARTORI, CLAUDIO
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
