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A fuzzy-based personalized recommender system for local businesses

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

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Abstract

© 2016 ACM. 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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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Tsai, CHCHT77@pitt.eduCHT770000-0001-9188-0362
Date: 10 July 2016
Date Type: Publication
Journal or Publication Title: HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media
Page Range: 297 - 302
Event Type: Conference
DOI or Unique Handle: 10.1145/2914586.2914641
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781450342476
Date Deposited: 27 Jul 2016 19:15
Last Modified: 22 Jan 2019 22:55
URI: http://d-scholarship.pitt.edu/id/eprint/28986

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