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A probabilistic retrieval model for semistructured data

conference contribution
posted on 2024-10-31, 15:44 authored by Jinyoung Kim, Xiaobing Xue, Bruce Croft
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.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1007/978-3-642-00958-7_22
  2. 2.
    ISBN - Is published in 9783642009570 (urn:isbn:9783642009570)

Start page

228

End page

239

Total pages

12

Outlet

Proceedings of the 31st European Conference on Information Retrieval (ECIR 09)

Editors

Mohand Boughanem, Catherine Berrut, Josiane Mothe and Chantal Soule-Dupuy

Name of conference

31st European Conference on Information Retrieval (ECIR 09)

Publisher

Springer

Place published

Berlin, Germany

Start date

2009-04-06

End date

2009-04-09

Language

English

Copyright

© Sringer-Verlag Berlin Heidelberg 2009

Former Identifier

2006024325

Esploro creation date

2020-06-22

Fedora creation date

2011-10-28

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