Analysis of adjective-noun word pair extraction methods for online review summarization

  • Authors:
  • Koji Yatani;Michael Novati;Andrew Trusty;Khai N. Truong

  • Affiliations:
  • Department of Computer Science, University of Toronto, Toronto, Canada;Department of Computer Science, University of Toronto, Toronto, Canada;Department of Computer Science, University of Toronto, Toronto, Canada;Department of Computer Science, University of Toronto, Toronto, Canada

  • Venue:
  • IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
  • Year:
  • 2011

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Abstract

Many people read online reviews written by other users to learn more about a product or venue. However, the overwhelming amount of user-generated reviews and variance in length, detail and quality across the reviews make it difficult to glean useful information. In this paper, we present a summarization system called Review Spotlight. It provides a brief overview of reviews by using adjective-noun word pairs extracted from the review text. The system also allows the user to click any word pair to read the original sentences from which the word pair was extracted. We present our system implementation as a Google Chrome browser extension, and an evaluation on how two word pair scoring methods (TF and TF-IDF) affect the identification of useful word pairs.