Model-based Feedback in the Language Modeling Approach to Information Retrieval

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Model-based Feedback in the Language Modeling Approach to Information Retrieval (2001)

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by Chengxiang Zhai , John Lafferty

Venue:	In Proceedings of Tenth International Conference on Information and Knowledge Management
Citations:	251 - 24 self

BibTeX

@INPROCEEDINGS{Zhai01model-basedfeedback,
    author = {Chengxiang Zhai and John Lafferty},
    title = {Model-based Feedback in the Language Modeling Approach to Information Retrieval},
    booktitle = {In Proceedings of Tenth International Conference on Information and Knowledge Management},
    year = {2001},
    pages = {403--410}
}

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Abstract

The language modeling approach to retrieval has been shown to perform well empirically. One advantage of this new approach is its statistical foundations. However, feedback, as one important component in a retrieval system, has only been dealt with heuristically in this new retrieval approach: the original query is usually literally expanded by adding ditional terms to it. Such expansion-based feedback creates an inconsistent interpretation of the original and the expanded query. In this paper, we present a more principled approach to feedback in the language modeling approach. Specifically, we treat feedback as updating the query language model based on the extra evidence carried by the feedback documents. Such a model-based feedback strategy easily fits into an extension of the language modeling approach. We propose and evaluate two different approaches to updating a query language model based on feedback documents, one based on a generarive probabilistic model of feedback documents and one based on minimization of the KL-divergence over feedback documents. Experiment resuits show that both approaches are effective and outperform the Rocchio feedback approach.

Keyphrases

feedback document information retrieval model-based feedback language modeling approach query language model generarive probabilistic model different approach experiment resuits new approach new retrieval approach ditional term original query extra evidence expansion-based feedback model-based feedback strategy inconsistent interpretation expanded query important component rocchio feedback approach statistical foundation principled approach retrieval system

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