Cotraining based bilingual sentiment lexicon learning

Dehong Gao, Furu Wei, Wenjie Li, Xiaohua Liu, Ming Zhou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

15 Citations (Scopus)

Abstract

In this paper, we address the issue of bilingual sentiment lexicon learning(BSLL) which aims to automatically and simultaneously generate sentiment words for two languages. The underlying motivation is that sentiment information from two languages can perform iterative mutual-teaching in the learning procedure. We propose to develop two classifiers to determine the sentiment polarities of words under a co-training framework, which makes full use of the two-view sentiment information from the two languages. The word alignment derived from the parallel corpus is leveraged to design effective features and to bridge the learning of the two classifiers. The experimental results on English and Chinese languages show the effectiveness of our approach in BSLL.
Original languageEnglish
Title of host publicationLate-Breaking Developments in the Field of Artificial Intelligence - Papers Presented at the 27th AAAI Conference on Artificial Intelligence, Technical Report
PublisherAI Access Foundation
Pages26-28
Number of pages3
VolumeWS-13-17
ISBN (Print)9781577356288
Publication statusPublished - 1 Jan 2013
Event27th AAAI Conference on Artificial Intelligence, AAAI 2013 - Bellevue, WA, United States
Duration: 14 Jul 201318 Jul 2013

Conference

Conference27th AAAI Conference on Artificial Intelligence, AAAI 2013
CountryUnited States
CityBellevue, WA
Period14/07/1318/07/13

ASJC Scopus subject areas

  • Engineering(all)

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