Conference Proceeding Article
Ranking businesses by competitiveness is useful in many applications including business (e.g., restaurant) recommendation, and estimation of intrinsic value of businesses for mergers and acquisitions. Our literature reveals that previous methods of business ranking have ignored the competing relationship among businesses within their geographical areas. To account for competition, we propose the use of PageRank model and its variant to derive the Competitive Rankof businesses. We use the check-ins of users from Foursquare, a location-based social network, to model the winners of competitions among stores. The results of our experiments show that Competitive Rank works well when evaluated against ground truth business ranking.
Computer Sciences | Databases and Information Systems
Data Management and Analytics
Social Computing, Behavioral-Cultural Modeling, and Prediction: 8th International Conference, SBP 2015, Washington, DC, USA, March 31-April 3, 2015: Proceedings
City or Country
DOAN THANH NAM; CHUA, Freddy Chong Tat; and Ee-peng LIM.
Mining Business Competitiveness from User Visitation Data. (2015). Social Computing, Behavioral-Cultural Modeling, and Prediction: 8th International Conference, SBP 2015, Washington, DC, USA, March 31-April 3, 2015: Proceedings. 9021, 283-289. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3109