@article{li-li-2013-novel,
    title = "A Novel Feature-based {B}ayesian Model for Query Focused Multi-document Summarization",
    author = "Li, Jiwei  and
      Li, Sujian",
    editor = "Lin, Dekang  and
      Collins, Michael",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "1",
    year = "2013",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/Q13-1008/",
    doi = "10.1162/tacl_a_00212",
    pages = "89--98",
    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."
}