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Combining Approaches to Information Retrieval

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Advances in Information Retrieval

Part of the book series: The Information Retrieval Series ((INRE,volume 7))

Abstract

The combination of different text representations and search strategies has become a standard technique for improving the effectiveness of information retrieval. combination, for example, has been studied extensively in the TREC evaluations and is the basis of the “meta-search” engines used on the Web. This paper examines the development of this technique, including both experimental results and the retrieval models that have been proposed as formal frameworks for combination. We show that combining approaches for information retrieval can be modeled as combining the outputs of multiple classifiers based on one or more representations, and that this simple model can provide explanations for many of the experimental results. We also show that this view of combination is very similar to the inference net model, and that a new approach to retrieval based on language models supports combination and can be integrated with the inference net model.

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  1. Department of Computer Science, University of Massachusetts, Amherst

    W. Bruce Croft

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    W. Bruce Croft

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© 2002 Kluwer Academic Publishers

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Croft, W.B. (2002). Combining Approaches to Information Retrieval. In: Croft, W.B. (eds) Advances in Information Retrieval. The Information Retrieval Series, vol 7. Springer, Boston, MA. https://doi.org/10.1007/0-306-47019-5_1

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  • DOI: https://doi.org/10.1007/0-306-47019-5_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-7923-7812-9

  • Online ISBN: 978-0-306-47019-6

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