Tsai, CH
(2016)
A fuzzy-based personalized recommender system for local businesses.
In: UNSPECIFIED.
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.
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