Detecting Spam Reviews for Improving House Sharing Recommendation

Ya Chu Chuang, Yung Ming Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

With the rapid development of technology, the business model of the tourism industry has changed. More and more people need to rent the houses, and it is easier for customers to use and get information on the Internet. In the era of Web 2.0, consumers can leave rating scores and write reviews on the online social platforms to share their experience with others. Nonetheless, there may exist some spam reviews. In this paper, we propose a novel approach to detect user profiles and spam reviews so as to generate a rental house recommendation. With this new mechanism, consumers can receive an appropriate recommendation from their own basic information, preference, and their close friends or family who are with powerful influence on them. Also, with the support of the proposed mechanism, less fake or useless reviews influence them.

Original languageEnglish
Title of host publicationProceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages91-94
Number of pages4
ISBN (Electronic)9781728126272
DOIs
StatePublished - Jul 2019
Event8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019 - Toyama, Japan
Duration: 7 Jul 201911 Jul 2019

Publication series

NameProceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019

Conference

Conference8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019
Country/TerritoryJapan
CityToyama
Period7/07/1911/07/19

Keywords

  • Recommendation systems
  • Semantic analysis
  • Sharing economy
  • Social influence
  • Spammer detection

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