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Journal of Intelligent Information Systems
Erschienen in: Journal of Intelligent Information Systems 3/2010

01.12.2010

Semantic-distance based evaluation of ranking queries over relational databases

verfasst von: Liang Zhu, Qin Ma, Chunnian Liu, Guojun Mao, Wenzhu Yang

Erschienen in: Journal of Intelligent Information Systems | Ausgabe 3/2010

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Abstract

Traditional database search uses pattern match in the comparison process. For a query with some search words, tuples are selected only if the words of the tuples exactly match the query words. In this paper, we propose a new method for evaluating relational ranking queries (or top-N queries) with text attributes. This method defines semantic distance functions and utilizes semantic match between words in database search. The attempt is that tuples, not only exactly matching, but also close to the query according to semantic distances, can both be fetched. The basic idea of the method is to create an index based on WordNet to expand the tuple words semantically. The candidate results for a query are retrieved by the index and a simple SQL selection statement, and then top-N answers are obtained. Extensive experiments are carried out to measure the performance of this new strategy for the evaluation of ranking queries over relational databases.
Vorheriger Artikel Ontology-driven web-based semantic similarity
Nächster Artikel Speed up gradual rule mining from stream data! A B-Tree and OWA-based approach

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Fußnoten
1
A relationship L on the sets X 1, ..., X k is a subset of their Cartesian product, written \(L \subseteq X_{1} \times \) ... ×X k .
 
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Metadaten
Titel
Semantic-distance based evaluation of ranking queries over relational databases
verfasst von
Liang Zhu
Qin Ma
Chunnian Liu
Guojun Mao
Wenzhu Yang
Publikationsdatum
01.12.2010
Verlag
Springer US
Erschienen in
Journal of Intelligent Information Systems / Ausgabe 3/2010
Print ISSN: 0925-9902
Elektronische ISSN: 1573-7675
DOI
https://doi.org/10.1007/s10844-009-0116-5

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