A state of the art opinion mining and its application domains

Author

Binali, Haji ; Potdar, Vidyasagar ; Wu, Chen

Author_Institution

Digital Ecosyst. & Bus. Intell. Inst., Curtin Univ. of Technol., Bentley, WA

fYear

2009

fDate

10-13 Feb. 2009

Firstpage

1

Lastpage

6

Abstract

This paper critically evaluates existing work, presents an opinion mining framework and exposes new areas of research in opinion mining. Individuals, businesses and government can now easily know the general opinion prevailing on a product, company or public policy. At the core of this field is semantic orientation of subjective terms in documents or reviews which seeks to establish their contextual connotation through opinion mining. Overall item sentiment can be expressed based on its sentiment words in general or by specifically identifying its features and the opinions being expressed about them. This leads us to the motivation of the framework for opinion mining and categorizing current literature in such a manner as to make clear, research opportunities. The freedom offered by the Web as a platform for presenting opinions on any subject brings with it many new opportunities.

Keywords

Internet; data mining; learning (artificial intelligence); Internet; contextual connotation; data mining; opinion mining; semantic orientation; supervised learning; unsupervised learning; Artificial intelligence; Data mining; Ecosystems; Humans; Information retrieval; Machine learning; Manufacturing industries; Supervised learning; Unsupervised learning; Visual databases; Opinion mining; data mining; supervised learning; unsupervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Technology, 2009. ICIT 2009. IEEE International Conference on

Conference_Location

Gippsland, VIC

Print_ISBN

978-1-4244-3506-7

Electronic_ISBN

978-1-4244-3507-4

Type

conf

DOI

10.1109/ICIT.2009.4939640

Filename

4939640