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<Paper uid="H05-1043">
  <Title>Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 339-346, Vancouver, October 2005. c(c)2005 Association for Computational Linguistics Extracting Product Features and Opinions from Reviews</Title>
  <Section position="5" start_page="344" end_page="345" type="relat">
    <SectionTitle>
4 Related Work
</SectionTitle>
    <Paragraph position="0"> The key components of OPINE described in this paper are the PMI feature assessment which leads to high-precision feature extraction and the use of relaxation-labeling in order to find the semantic orientation of potential opinion words. The review-mining work most relevant to our research is that of (Hu and Liu, 2004) and (Kobayashi et al., 2004). Both identify product features from reviews, but OPINE significantly improves on both. (Hu and Liu, 2004) doesn't assess candidate features, so its precision is lower than OPINE's. (Kobayashi et al., 2004) employs an iterative semi-automatic approach which requires human input at every iteration. Neither model explicitly addresses composite (feature of feature) or implicit features.</Paragraph>
    <Paragraph position="1"> Other systems (Morinaga et al., 2002; Kushal et al., 2003) also look at Web product reviews but they do not extract  opinions about particular product features. OPINE's use of meronymy lexico-syntactic patterns is similar to that of many others, from (Berland and Charniak, 1999) to (Almuhareb and Poesio, 2004).</Paragraph>
    <Paragraph position="2"> Recognizing the subjective character and polarity of words, phrases or sentences has been addressed by many authors, including (Turney, 2003; Riloff et al., 2003; Wiebe, 2000; Hatzivassiloglou and McKeown, 1997).</Paragraph>
    <Paragraph position="3"> Most recently, (Takamura et al., 2005) reports on the use of spin models to infer the semantic orientation of words. The paper's global optimization approach and use of multiple sources of constraints on a word's semantic orientation is similar to ours, but the mechanism differs and they currently omit the use of syntactic information.</Paragraph>
    <Paragraph position="4"> Subjective phrases are used by (Turney, 2002; Pang and Vaithyanathan, 2002; Kushal et al., 2003; Kim and Hovy, 2004) and others in order to classify reviews or sentences as positive or negative. So far, OPINE's focus has been on extracting and analyzing opinion phrases corresponding to specific features in specific sentences, rather than on determining sentence or review polarity.</Paragraph>
  </Section>
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