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Title

Query relaxation for star queries on RDF

Author(s)

Huang, Hai;  Liu, Chengfei

Abstract

Query relaxation is an important problem for querying RDF data flexibly. The previous work mainly uses ontology information for relaxing user queries. The ranking models proposed, however, are either non-quantifiable or imprecise. Furthermore, the recommended relaxed queries may return no results. In this paper, we aim to solve these problems by proposing a new ranking model. The model ranks the relaxed queries according to their similarities to the original user query. The similarity of a relaxed query to the original query is measured based on the difference of their estimated results. To compute similarity values for star queries efficiently and precisely, Bayesian networks are employed to estimate the result numbers of relaxed queries. An algorithm is also proposed for answering top-k queries. At last experiments validate the effectiveness of our method.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies

Source

Lecture notes in computer science: proceedings of the 11th International Conference on Web Information Systems Engineering (WISE 2010), Hong Kong, China, 12-14 December 2010 / Lei Chan, Peter Triantafillou and Torsten Suel (eds.), Vol. 6488, pp. 376-389

Publication year

2010

FOR Code(s)

0805 Distributed Computing

Keyword(s)

Query relaxation;  RDF query processing;  Resource description framework

Publisher

Springer

ISSN

0302-9743 (series ISSN)

ISBN

9783642176159, 3642176151

Publisher URL

http://dx.doi.org/10.1007/978-3-642-17616-6_34

Copyright

Copyright © Springer-Verlag Berlin Heidelberg 2010. The accepted manuscript of the paper is reproduced here in accordance with the copyright policy of the publisher. The definitive version of the publication is available at www.springer.com.

Research Projects

XML views of relational databases: semantics and update problems, Australian Research Council grant number DP878405

Full text

Peer reviewed