Author ORCID Identifier
Document Type
Conference Proceeding
Publication Date
7-2016
Publication Title
HT : Proceedings of the 27th ACM Conference on Hypertext and Social Media
Volume
July 2016
First Page
297
Last Page
302
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.
Recommended Citation
Tsai, Chun-Hua, "A Fuzzy-Based Personalized Recommender System for Local Businesses" (2016). Information Systems and Quantitative Analysis Faculty Publications. 148.
https://digitalcommons.unomaha.edu/isqafacpub/148
Comments
© {Author | ACM} {2016}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in {HT : Proceedings of the 27th ACM Conference on Hypertext and Social Media}, https://doi.org/10.1145/2914586.2914641