Unsupervised discovery of discourse relations for eliminating intra-sentence polarity ambiguities

Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam Fai Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

49 Citations (Scopus)

Abstract

Polarity classification of opinionated sentences with both positive and negative senti-ments1 is a key challenge in sentiment analysis. This paper presents a novel unsuper-vised method for discovering intra-sentence level discourse relations for eliminating polarity ambiguities. Firstly, a discourse scheme with discourse constraints on polarity was defined empirically based on Rhetorical Structure Theory (RST). Then, a small set of cue-phrase-based patterns were utilized to collect a large number of discourse instances which were later converted to semantic sequential representations (SSRs). Finally, an unsuper-vised method was adopted to generate, weigh and filter new SSRs without cue phrases for recognizing discourse relations. Experimental results showed that the proposed methods not only effectively recognized the defined discourse relations but also achieved significant improvement by integrating discourse information in sentence-level polarity classification.

Original languageEnglish
Title of host publicationEMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
Pages162-171
Number of pages10
Publication statusPublished - 3 Oct 2011
Externally publishedYes
EventConference on Empirical Methods in Natural Language Processing, EMNLP 2011 - Edinburgh, United Kingdom
Duration: 27 Jul 201131 Jul 2011

Other

OtherConference on Empirical Methods in Natural Language Processing, EMNLP 2011
CountryUnited Kingdom
CityEdinburgh
Period27/7/1131/7/11

Fingerprint

Semantics

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

Cite this

Zhou, L., Li, B., Gao, W., Wei, Z., & Wong, K. F. (2011). Unsupervised discovery of discourse relations for eliminating intra-sentence polarity ambiguities. In EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 162-171)

Unsupervised discovery of discourse relations for eliminating intra-sentence polarity ambiguities. / Zhou, Lanjun; Li, Binyang; Gao, Wei; Wei, Zhongyu; Wong, Kam Fai.

EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. 2011. p. 162-171.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhou, L, Li, B, Gao, W, Wei, Z & Wong, KF 2011, Unsupervised discovery of discourse relations for eliminating intra-sentence polarity ambiguities. in EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. pp. 162-171, Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, Edinburgh, United Kingdom, 27/7/11.
Zhou L, Li B, Gao W, Wei Z, Wong KF. Unsupervised discovery of discourse relations for eliminating intra-sentence polarity ambiguities. In EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. 2011. p. 162-171
Zhou, Lanjun ; Li, Binyang ; Gao, Wei ; Wei, Zhongyu ; Wong, Kam Fai. / Unsupervised discovery of discourse relations for eliminating intra-sentence polarity ambiguities. EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. 2011. pp. 162-171
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