Automatic domain ontology extraction for context-sensitive opinion mining

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Title of host publicationICIS 2009 Proceedings - Thirtieth International Conference on Information Systems
Publication statusPublished - 2009

Conference

Title30th International Conference on Information Systems, ICIS 2009
PlaceUnited States
CityPhoenix
Period15 - 18 December 2009

Abstract

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations' business strategy development and individual consumers' comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context-sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based context-sensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.

Research Area(s)

  • Domain ontology, Fuzzy sets, Kullback-leibler divergence, Ontology extraction, Opinion mining, Sentiment analysis, Sentiment context

Citation Format(s)

Automatic domain ontology extraction for context-sensitive opinion mining. / Lau, Raymond Y.K.; Ma, Jian; Lai, Chapmann C.L.; Li, Yuefeng.

ICIS 2009 Proceedings - Thirtieth International Conference on Information Systems. 2009.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review