Extracting Relevant Attribute Values for Improved Search

Sonia Bergamaschi, Claudio Sartori, Francesco Guerra, Mirko Orsini · IEEE Internet Computing · 2007

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.

Read the paper · More papers on PaperTik