DocumentCode
3439434
Title
A Framework of Review Analysis for Enhancement of Business Decision Making
Author
Qazi, Atika ; Raj, Raghu G. ; Tahir, M. ; Naqvi, Syed Ghaour Abbas
Author_Institution
Univ. of Malaya, Kuala Lumpur, Malaysia
fYear
2013
fDate
7-10 Dec. 2013
Firstpage
955
Lastpage
958
Abstract
In order to remain competitive, modern businesses must keep informed about consumers´ opinions via web-based reviews or similar channels. Today, the usefulness factor in opinion mining is mainly achieved through helpful user ratings in reviews. Reviews belong to different categories and each category contains different types of information that have not yet been the focus of sentiment analysis research so far. There is useful content in each type of review that may be helpful to users as well as designers. Therefore, it is essential to classify reviews into multiple types and then share relevant information with people involved in the development of business products and services. We hereby propose a review analysis framework, which may help designers and customers to extract useful information from user-generated contents. The proposed framework aims to enable users, designers and potential buyers to enhance decision making strategies and, hence, and improve business intelligence.
Keywords
Internet; competitive intelligence; data mining; decision making; reviews; Web; business decision making enhancement; business intelligence improvement; business products; business services; opinion mining; review analysis framework; sentiment analysis research; user ratings; user-generated contents; Computational linguistics; Conferences; Data mining; Decision making; Motion pictures; Pragmatics; Business Intelligence; Opinion Mining; Review Analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on
Conference_Location
Dallas, TX
Print_ISBN
978-1-4799-3143-9
Type
conf
DOI
10.1109/ICDMW.2013.160
Filename
6754024
Link To Document