Feature extraction of travel destinations from online Chinese-language customer reviews

Qiang Ye, Chun Hung Roberts Law, Shi Li, Yijun Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)

Abstract

Many customers presently browse a large number of online reviews prior to making purchase decisions to access the word-of-mouth comments of other customers about the products and services in which they are interested. Therefore, online customer reviews serve as a feedback mechanism that can help suppliers to improve their products and services, thus gaining competitive advantages. More specifically, the product feature extractions from such reviews are expected to further illuminate the views and attitudes of customers. This study analyses the customer reviews that are posted by Chinese speakers about travel destinations. Our new approach is based on a recently introduced data mining approach that further explores reviews about travel destinations as a particular type of product. Experiments were conducted using datasets comprised of the reviews of three travel destinations in mainland China that had been posted on the internet. The empirical results prove the validity of the proposed method.
Original languageEnglish
Pages (from-to)106-118
Number of pages13
JournalInternational Journal of Services, Technology and Management
Volume15
Issue number1-2
DOIs
Publication statusPublished - 1 Feb 2011

Keywords

  • Data mining
  • Product features
  • Travel destination reviews

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Strategy and Management
  • Marketing

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