Paper: Unsupervised Discovery of Discourse Relations for Eliminating Intra-sentence Polarity Ambiguities

ACL ID D11-1015
Title Unsupervised Discovery of Discourse Relations for Eliminating Intra-sentence Polarity Ambiguities
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

Polarity classification of opinionated sen- tences with both positive and negative senti- ments 1 is a key challenge in sentiment anal- ysis. This paper presents a novel unsuper- vised method for discovering intra-sentence level discourse relations for eliminating polar- ity ambiguities. Firstly, a discourse scheme with discourse constraints on polarity was de- fined empirically based on Rhetorical Struc- ture 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. Experimen- tal results showed that the propos...