Joint promotion partner recommendation systems using data from location-based social networks

Yi Chung Chen, Hsi Ho Huang, Sheng Min Chiu, Chiang Lee

Research output: Contribution to journalArticlepeer-review

Abstract

Joint promotion is a valuable business strategy that enables companies to attract more customers at lower operational cost. However, finding a suitable partner can be extremely difficult. Conventionally, one of the most common approaches is to conduct survey-based analysis; however, this method can be unreliable as well as time-consuming, considering that there are likely to be thousands of potential partners in a city. This article proposes a framework to recommend Joint Promotion Partners using location-based social networks (LBSN) data. We considered six factors in determining the suitability of a partner (customer base, association, rating and awareness, prices and star ratings, distance, and promotional strategy) and developed efficient algorithms to perform the required calculations. The effectiveness and efficiency of our algorithms were verified using the Foursquare dataset and real-life case studies.

Original languageEnglish
Article number57
JournalISPRS International Journal of Geo-Information
Volume10
Issue number2
DOIs
Publication statusPublished - 2021 Feb 1

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)

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