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Automatic Text Summarization with a Reduced Vocabulary Using Continuous Space Vectors

  • Elvys Linhares PontesEmail author
  • Stéphane Huet
  • Juan-Manuel Torres-Moreno
  • Andréa Carneiro Linhares
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9612)

Abstract

In this paper, we propose a new method that uses continuous vectors to map words to a reduced vocabulary, in the context of Automatic Text Summarization (ATS). This method is evaluated on the MultiLing corpus by the ROUGE evaluation measures with four ATS systems. Our experiments show that the reduced vocabulary improves the performance of state-of-the-art systems.

Keywords

Word embedding Text summarization Vocabulary reduction 

References

  1. 1.
    Balikas, G., Amini, M.R.: Learning language-independent sentence representations for multi-lingual, multi-document summarization. In: 17ème Conférence Francophone sur l’Apprentissage Automatique (CAp) (2015)Google Scholar
  2. 2.
    Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: SIGIR, pp. 335–336 (1998)Google Scholar
  3. 3.
    Collobert, R., Weston, J.: A unified architecture for natural language processing: deep neural networks with multitask learning. In: ICML, pp. 160–167 (2008)Google Scholar
  4. 4.
    Giannakopoulos, G., El-Haj, M., Favre, B., Litvak, M., Steinberger, J., Varma, V.: TAC2011 multiling pilot overview. In: TAC (2011)Google Scholar
  5. 5.
    Kågebäck, M., Mogren, O., Tahmasebi, N., Dubhashi, D.: Extractive summarization using continuous vector space models. In: 2nd EACL Workshop on Continuous Vector Space Models and their Compositionality (CVSC), pp. 31–39 (2014)Google Scholar
  6. 6.
    Lin, C.Y.: ROUGE: a package for automatic evaluation of summaries. In: ACL Workshop on Text Summarization Branches Out (2004)Google Scholar
  7. 7.
    Mihalcea, R., Tarau, P.: Textrank: bringing order into texts. In: EMNLP, pp. 404–411 (2004)Google Scholar
  8. 8.
    Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: NIPS, pp. 3111–3119 (2013)Google Scholar
  9. 9.
    Pennington, J., Socher, R., Manning, C.: Glove: Global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532–1543. Association for Computational Linguistics, Doha, October 2014Google Scholar
  10. 10.
    Phung, V., De Vine, L.: A study on the use of word embeddings and pagerank for vietnamese text summarization. In: 20th Australasian Document Computing Symposium, pp. 7:1–7:8 (2015)Google Scholar
  11. 11.
    Pontes, E.L., Linhares, A.C., Torres-Moreno, J.M.: Sasi: sumarizador automático de documentos baseado no problema do subconjunto independente de vértices. In: XLVI Simpósio Brasileiro de Pesquisa Operacional (2014)Google Scholar
  12. 12.
    Torres-Moreno, J.M.: Automatic Text Summarization. Wiley, Hoboken (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Elvys Linhares Pontes
    • 1
    Email author
  • Stéphane Huet
    • 1
  • Juan-Manuel Torres-Moreno
    • 1
    • 2
  • Andréa Carneiro Linhares
    • 3
  1. 1.LIAUniversité d’Avignon et des Pays de VaucluseAvignonFrance
  2. 2.École Polytechnique de MontréalMontréalCanada
  3. 3.Universidade Federal do CearáSobralBrazil

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