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Opinion Mining as Extraction of Attribute-Value Relations

  • Nozomi Kobayashi
  • Ryu Iida
  • Kentaro Inui
  • Yuji Matsumoto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4012)

Abstract

This paper addresses the task of extracting opinions from a given document collection. Assuming that an opinion can be represented as a tuple 〈Subject, Attribute, Value〉, we propose a computational method to extract such tuples from texts. In this method, the main task is decomposed into (a) the process of extracting Attribute-Value pairs from a given text and (b) the process of judging whether an extracted pair expresses an opinion of the author. We apply machine-learning techniques to both subtasks. We also report on the results of our experiments and discuss future directions.

Keywords

Noun Phrase Machine Translation Opinion Mining Sentiment Analysis Opinion Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nozomi Kobayashi
    • 1
  • Ryu Iida
    • 1
  • Kentaro Inui
    • 1
  • Yuji Matsumoto
    • 1
  1. 1.Nara Institute of Science and TechnologyNaraJapan

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