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 language | English |
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Title of host publication | The Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018 |
Publisher | International World Wide Web Conferences Steering Committee |
Pages | 121-122 |
ISBN (Electronic) | 9781450356404 |
DOIs | |
Publication status | Published - 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/10.1145/3184558.3186959Keywords
- Abstractive summarization
- Extractive summarization
- Sequenceto-sequence framework