A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization
Computation and Language
2013-12-30 v2 Information Retrieval
Abstract
Both supervised learning methods and LDA based topic model have been successfully applied in the field of query focused 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. Experiments on TAC2008 and TAC2009 demonstrate the effectiveness of our approach.
Cite
@article{arxiv.1212.2006,
title = {A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization},
author = {Jiwei Li and Sujian Li},
journal= {arXiv preprint arXiv:1212.2006},
year = {2013}
}
Comments
This paper has been withdrawn by the author due to a crucial sign error in equation