A probabilistic retrieval model for semistructured data

Kim, J, Xue, X and Croft, B 2009, 'A probabilistic retrieval model for semistructured data', in Mohand Boughanem, Catherine Berrut, Josiane Mothe and Chantal Soule-Dupuy (ed.) Proceedings of the 31st European Conference on Information Retrieval (ECIR 09), Toulouse, France, 6-9 April 2009, pp. 228-239.


Document type: Conference Paper
Collection: Conference Papers

Title A probabilistic retrieval model for semistructured data
Author(s) Kim, J
Xue, X
Croft, B
Year 2009
Conference name 31st European Conference on Information Retrieval (ECIR 09)
Conference location Toulouse, France
Conference dates 6-9 April 2009
Proceedings title Proceedings of the 31st European Conference on Information Retrieval (ECIR 09)
Editor(s) Mohand Boughanem, Catherine Berrut, Josiane Mothe and Chantal Soule-Dupuy
Publisher Springer
Place of publication Berlin, Germany
Start page 228
End page 239
Total pages 12
Abstract Retrieving semistructured (XML) data typically requires either a structured query such as XPath, or a keyword query that does not take structure into account. In this paper, we infer structural information automatically from keyword queries and incorporate this into a retrieval model. More specifically, we propose the concept of a mapping probability, which maps each query word into a related field (or XML element). This mapping probability is used as a weight to combine the language models estimated from each field. Experiments on two test collections show that our retrieval model based on mapping probabilities outperforms baseline techniques significantly.
Subjects Information Systems not elsewhere classified
DOI - identifier 10.1007/978-3-642-00958-7_22
Copyright notice © Sringer-Verlag Berlin Heidelberg 2009
ISBN 9783642009570
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Citation counts: TR Web of Science Citation Count  Cited 21 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 40 times in Scopus Article | Citations
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