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        <title>A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization</title>
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    <name type="personal">
        <namePart type="given">Jiwei</namePart>
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    <abstract>Supervised learning methods and LDA based topic model have been successfully applied in the field of multi-document summarization. In this paper, we propose a novel supervised approach that can incorporate rich sentence features into Bayesian topic models in a principled way, thus taking advantages of both topic model and feature based supervised learning methods. Experimental results on DUC2007, TAC2008 and TAC2009 demonstrate the effectiveness of our approach.</abstract>
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%0 Journal Article
%T A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization
%A Li, Jiwei
%A Li, Sujian
%J Transactions of the Association for Computational Linguistics
%D 2013
%V 1
%I MIT Press
%C Cambridge, MA
%F li-li-2013-novel
%X Supervised learning methods and LDA based topic model have been successfully applied in the field of multi-document summarization. In this paper, we propose a novel supervised approach that can incorporate rich sentence features into Bayesian topic models in a principled way, thus taking advantages of both topic model and feature based supervised learning methods. Experimental results on DUC2007, TAC2008 and TAC2009 demonstrate the effectiveness of our approach.
%R 10.1162/tacl_a_00212
%U https://aclanthology.org/Q13-1008
%U https://doi.org/10.1162/tacl_a_00212
%P 89-98

Markdown (Informal)

[A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization](https://aclanthology.org/Q13-1008) (Li & Li, TACL 2013)

• A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization (Li & Li, TACL 2013)

ACL

• Jiwei Li and Sujian Li. 2013. A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization. Transactions of the Association for Computational Linguistics, 1:89–98.