Query relaxation for star queries on RDF

Authors:
Hai Huang;Chengfei Liu
Affiliations:
Faculty of ICT, Swinburne University of Technology, VIC, Australia;Faculty of ICT, Swinburne University of Technology, VIC, Australia
Venue:
WISE'10 Proceedings of the 11th international conference on Web information systems engineering
Year:
2010

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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.