Article

User biased document language modelling

Authors:

C. J. van RijsbergenAuthors Info & Claims

SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 542 - 543

https://doi.org/10.1145/1008992.1009111

Published: 25 July 2004 Publication History

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Abstract

Capitalizing on the intuitive underlying assumptions of Language Modelling for Ad-Hoc Retrieval we present a novel approach that is capable of injecting the user's context of the document collection into the retrieval process. The preliminary findings from the evaluation undertaken suggest that improved IR performance is possible under certain circumstances. This motivates further investigation to determine the extent and significance of this improved performance.

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J. M. Ponte and W. B. Croft. A language modeling approach to information retrieval. In 21st ACM SIGIR Conference, pages 275--281, Melbourne, Australia, 1998.

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K. Sparck-Jones, S. Walker, and S. E. Robertson. A probabilistic model of information retrieval: development and comparative experiments. Information Processing and Managament, 36:779--808, 2000.

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C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In 24th ACM SIGIR Conference, pages 49--56, New Orleans, LO, 2001.

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C. Zhai and J. Lafferty. Two-stage language models for infromation retrieval. In 25th ACM SIGIR Conference, pages 49--56, Tampere, Finland, 2002.

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Index Terms

User biased document language modelling
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Published In

SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

July 2004

624 pages

ISBN:1581138814

DOI:10.1145/1008992

General Chair:
Mark Sanderson
University of Sheffield (UK)
,
Program Chairs:
Kalervo Järvelin
University of Tampere (Finland)
,
James Allan
University of Massachusetts (USA)
,
Peter Bruza
Distributed Systems Technology Centre (Australia)

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 July 2004

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SIGIR04: The 27th ACM/SIGIR International Symposium on Information Retrieval 2004

July 25 - 29, 2004

Sheffield, United Kingdom

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Recommendations

The Study of Methods for Language Model Based Positive and Negative Relevance Feedback in Information Retrieval

Cluster-based retrieval using language models

Passage retrieval based on language models

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