An effective joint framework for document summarization

Min GUI, Zhengkun ZHANG, Zhenglu YANG, Yanhui GU, Guandong XU

Research output: Chapter in Book/Report/Conference proceedingChapters

4 Citations (Scopus)

Abstract

Document summarization is an important research issue and has attracted much attention from the academe. The approaches for document summarization can be classified as extractive and abstractive. In this work, we introduce an effective joint framework that integrates extractive and abstractive summarization models, which is much closer to the way human write summaries (first underlining important information). Preliminary experiments on real benchmark dataset demonstrate that our model is competitive with the state-of-the-art methods. Copyright © 2018 IW3C2 (International World Wide Web Conference Committee).

Original languageEnglish
Title of host publicationThe Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018
PublisherInternational World Wide Web Conferences Steering Committee
Pages121-122
ISBN (Electronic)9781450356404
DOIs
Publication statusPublished - Apr 2018

Citation

Gui, M., Zhang, Z., Yang, Z., Gu, Y., & Xu, G. (2018). An effective joint framework for document summarization. In The Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018 (pp. 121-122). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3184558.3186959

Keywords

  • Abstractive summarization
  • Extractive summarization
  • Sequenceto-sequence framework

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