Chinese document re-ranking based on automatically acquired term resource |
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Authors: | Donghong Ji Shiju Zhao Guozheng Xiao |
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Affiliation: | (1) Department of Computer Science, Center for Study of Language Information, Wuhan University, 430072 Wuhan, China;(2) Department of Chinese Language and Literature, Wuhan University, 430072 Wuhan, China;(3) Center for Study of Language Information, Wuhan University, 430072 Wuhan, China |
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Abstract: | In this paper, we address the problem of document re-ranking in information retrieval, which is usually conducted after initial
retrieval to improve rankings of relevant documents. To deal with this problem, we propose a method which automatically constructs
a term resource specific to the document collection and then applies the resource to document re-ranking. The term resource
includes a list of terms extracted from the documents as well as their weighting and correlations computed after initial retrieval.
The term weighting based on local and global distribution ensures the re-ranking not sensitive to different choices of pseudo
relevance, while the term correlation helps avoid any bias to certain specific concept embedded in queries. Experiments with
NTCIR3 data show that the approach can not only improve performance of initial retrieval, but also make significant contribution
to standard query expansion. |
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Keywords: | |
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