Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
4-2015
Abstract
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.
Discipline
Computer Sciences | Databases and Information Systems
Publication
Social Computing, Behavioral-Cultural Modeling, and Prediction: 8th International Conference, SBP 2015, Washington, DC, USA, March 31-April 3, 2015: Proceedings
Volume
9021
First Page
283
Last Page
289
ISBN
9783319162676
Identifier
10.1007/978-3-319-16268-3_31
Publisher
Springer Verlag
City or Country
Cham
Citation
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.
Available at: https://ink.library.smu.edu.sg/sis_research/3109
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1007/978-3-319-16268-3_31