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2007

Measuring Importance and Query Relevance in Topic-focused Multi-document Summarization

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Measuring Importance and Query Relevance in Topic-focused Multi-document Summarization
The increasing complexity of summarization systems makes it difficult to analyze exactly which modules make a difference in performance. We carried out a principled comparison between the two most commonly used schemes for assigning importance to words in the context of query focused multi-document summarization: raw frequency (word probability) and log-likelihood ratio. We demonstrate that the advantages of log-likelihood ratio come from its known distributional properties which allow for the identification of a set of words that in its entirety defines the aboutness of the input. We also find that LLR is more suitable for query-focused summarization since, unlike raw frequency, it is more sensitive to the integration of the information need defined by the user.
Surabhi Gupta, Ani Nenkova, Daniel Jurafsky
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ACL
Authors Surabhi Gupta, Ani Nenkova, Daniel Jurafsky
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