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A proposal for efficient automatic summarization of online product reviews

Published:04 January 2018Publication History

ABSTRACT

A popular application of social data mining is sentiment detection or opinion analysis of consumer products or social events. In this work, a proposal for automatic summarization of a set of online review data on a particular consumer product is outlined so that the overall quality of the product can be assessed without going through all the reviews manually one by one. In this approach the most discussed aspects of the products will be highlighted in a constructed manner.

References

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  3. Mohammad Ali Abbasi Reza Zafarani and Huan Liu. 2014. Social Media Mining: An Introduction. Cambridge University Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Xiaofeng He-Aoying Zhou Rong Zhang, Zhenjie Zhang. 2015. Dish Comment Summarization Based on Bilateral Topic Analysis. In Proceedings of the 31st IEEE International Conference on Data Engineering (ICDE). 483--494.Google ScholarGoogle Scholar
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  1. A proposal for efficient automatic summarization of online product reviews

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    • Published in

      cover image ACM Other conferences
      Workshops ICDCN '18: Proceedings of the Workshop Program of the 19th International Conference on Distributed Computing and Networking
      January 2018
      151 pages
      ISBN:9781450363976
      DOI:10.1145/3170521
      • Conference Chair:
      • Doina Bein

      Copyright © 2018 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 4 January 2018

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