Using an opinion mining approach to exploit Web content in order to improve customer relationship management

A traditional market survey typically seeks out customers' opinions using voluntary questionnaires or focus group interviews. The surveys' perceived and actual reliability could be limited by the number of customers who choose to respond, bias inherent in the wording of the questions or th...

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Bibliographic Details
Main Authors: Kongthon, Alisa, Angkawattanawit, Niran, Sangkeettrakarn, Chatchawal, Palingoon, Pornpimon, Haruechaiyasak, Choochart
Format: Conference Proceeding
Language:English
Subjects:
Customer satisfaction
Data mining
Feature extraction
Humans
Internet
Online Access:Request full text
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Summary:A traditional market survey typically seeks out customers' opinions using voluntary questionnaires or focus group interviews. The surveys' perceived and actual reliability could be limited by the number of customers who choose to respond, bias inherent in the wording of the questions or the subjects' interpretation regarding the information being sought. Online opinion resources such as review sites, forums, discussion groups and blogs are available with increasing variety and popularity. Companies can now apply information retrieval, natural language processing and machine learning techniques to automatically and more objectively identify and understand the opinions of their customers. In this paper, we present an approach to analyze customers' opinions regarding the hotels in Thailand. Such results can be used to determine public perceptions regarding selected hotels in order to allow the business to better understand customer satisfaction.
ISSN:2159-5100