A fuzzy-based personalized recommender system for local businesses

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

On-line reviewing systems have become prevalent in our society. User-provided reviews of local businesses have provided rich information in terms of users' preferences regarding businesses and their interactions in reviewing systems; however, little is known about how the reviewing behaviors of users can benefit businesses in terms of suggesting potential collaboration opportunities. In the current study, we aim to build a recommendation system for businesses to provide suggestions for business collaboration. Based on historical data from Yelp that shows two businesses being reviewed by the same users within a same season, we were able to identify businesses that might attract the same customers in the future, and hence provide them with a collaboration suggestion. Our results suggest that the evidence-two businesses sharing reviews from same users-can provide recommendations for businesses to pursue future collaborative marketing opportunities.

Original languageEnglish (US)
Title of host publicationHT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media
PublisherAssociation for Computing Machinery, Inc
Pages297-302
Number of pages6
ISBN (Electronic)9781450342476
DOIs
StatePublished - Jul 10 2016
Event27th ACM Conference on Hypertext and Social Media, HT 2016 - Halifax, Canada
Duration: Jul 10 2016Jul 13 2016

Publication series

NameHT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media

Other

Other27th ACM Conference on Hypertext and Social Media, HT 2016
CountryCanada
CityHalifax
Period7/10/167/13/16

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All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software
  • Artificial Intelligence

Cite this

Tsai, C. H. (2016). A fuzzy-based personalized recommender system for local businesses. In HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media (pp. 297-302). (HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media). Association for Computing Machinery, Inc. https://doi.org/10.1145/2914586.2914641