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Combining Probabilistic Language Models for Aspect-Based Sentiment Retrieval

  • Lisette García-Moya
  • Henry Anaya-Sánchez
  • Rafael Berlanga-Llavori
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7224)

Abstract

In this paper, we present a new methodology aimed at retrieving relevant product aspects from a collection of customer reviews, as well as the most salient sentiments expressed about them. Our proposal is both unsupervised and domain independent, and does not relies on NLP techniques such as parsing or dependence analysis. In our experiments, the proposed method achieves good values of precision. It is also shown that our approach is capable of properly retrieving the relevant aspects and their sentiments even from individual reviews.

Keywords

Sentiment analysis aspect retrieval language models 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Lisette García-Moya
    • 1
  • Henry Anaya-Sánchez
    • 1
  • Rafael Berlanga-Llavori
    • 1
  1. 1.Universitat Jaume ISpain

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