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Multilingual Multi-document Summarization with Enhanced hLDA Features

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Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data (NLP-NABD 2016, CCL 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10035))

Abstract

This paper presents the state of art research progress on multilingual multi-document summarization. Our method utilizes hLDA (hierarchical Latent Dirichlet Allocation) algorithm to model the documents firstly. A new feature is proposed from the hLDA modeling results, which can reflect semantic information to some extent. Then it combines this new feature with different other features to perform sentence scoring. According to the results of sentence score, it extracts candidate summary sentences from the documents to generate a summary. We have also attempted to verify the effectiveness and robustness of the new feature through experiments. After the comparison with other summarization methods, our method reveals better performance in some respects.

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Acknowledgement

This work was supported by the National Natural Science Foundation of China under Grant 91546121, 61202247, 71231002 and 61472046; EU FP7 IRSES MobileCloud Project (Grant No. 612212); the 111 Project of China under Grant B08004; Engineering Research Center of Information Networks, Ministry of Education; Beijing Institute of Science and Technology Information; CapInfo Company Limited.

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Authors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Taiwen Huang, Lei Li & Yazhao Zhang

Authors
  1. Taiwen Huang
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  2. Lei Li
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  3. Yazhao Zhang
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Corresponding author

Correspondence to Taiwen Huang .

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Editors and Affiliations

  1. Tsinghua University , Beijing, China

    Maosong Sun

  2. Fudan University , Shanghai, China

    Xuanjing Huang

  3. Dalian University of Technology , Dalian, China

    Hongfei Lin

  4. Tsinghua University , Beijing, China

    Zhiyuan Liu

  5. Tsinghua University , Beijing, China

    Yang Liu

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Huang, T., Li, L., Zhang, Y. (2016). Multilingual Multi-document Summarization with Enhanced hLDA Features. In: Sun, M., Huang, X., Lin, H., Liu, Z., Liu, Y. (eds) Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data. NLP-NABD CCL 2016 2016. Lecture Notes in Computer Science(), vol 10035. Springer, Cham. https://doi.org/10.1007/978-3-319-47674-2_25

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  • DOI: https://doi.org/10.1007/978-3-319-47674-2_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47673-5

  • Online ISBN: 978-3-319-47674-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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