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Asia Information Retrieval Symposium

AIRS 2014: Information Retrieval Technology pp 256–267Cite as

Contrastive Max-Sum Opinion Summarization

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8870))

Abstract

People can reach all kinds of information online incuding reviews and comments on products, movies, holiday destinations and so on. However, one usually need to go through the reviews to have an objective opinion the positive and the negative aspects of the item reviewed. We aim to provie a method that will extract positive and negative opinions on a specific aspect and compare them in an attempt to ease on the information overflow. Contrastive opinion summarization (COS) aims to solve this issue. COS methods extract representative and comparative sentences in terms of specific aspects of a product. In this paper, we propose a new COS method, namely Contrastive Max-Sum Opinion Summarization (CMSOS). This method considers representativeness and contrastiveness at the same time. For the evaluation, we use an English dataset which was specifically created for COS studies. In addition, we created a new dataset in Turkish and shared it publicly. We provide the results on both datasets with our method.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Makbule Gülçin Özsoy & Ruket Çakıcı

Authors
  1. Makbule Gülçin Özsoy
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  2. Ruket Çakıcı
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Editor information

Editors and Affiliations

  1. Institute of Visual Informatic, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Azizah Jaafar

  2. Institute of Visual Informatics, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Nazlena Mohamad Ali

  3. Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Shahrul Azman Mohd Noah

  4. Insight Centre for Data Analytics, Dublin City University, Glasnevin, 9, Dublin, Ireland

    Alan F. Smeaton

  5. Information Systems, Queensland University of Technology, 4001, Brisbane, QLD, Australia

    Peter Bruza

  6. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia

    Zainab Abu Bakar  & Nursuriati Jamil  & 

  7. Cyber Security Center, Universiti Pertahanan Nasional Malaysia, Kem Sungai Besi, 57000, Kuala Lumpur, Malaysia

    Tengku Mohd Tengku Sembok

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© 2014 Springer International Publishing Switzerland

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Özsoy, M.G., Çakıcı, R. (2014). Contrastive Max-Sum Opinion Summarization. In: Jaafar, A., et al. Information Retrieval Technology. AIRS 2014. Lecture Notes in Computer Science, vol 8870. Springer, Cham. https://doi.org/10.1007/978-3-319-12844-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-12844-3_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12843-6

  • Online ISBN: 978-3-319-12844-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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