PLUTUS: Leveraging location-based social networks to recommend potential customers to venues

Mohamed Sarwat, Ahmed Eldawy, Mohamed F Mokbel, John Riedl

Research output: Contribution to journalConference article

16 Scopus citations

Abstract

In a business setting, the customer value is crucial as it determines how much it is worth spending to acquire a particular customer. Viral marketing techniques leverages social ties among users to help advertising a particular product. Recently, as mobile devices (e.g., smart phones, GPS devices) became ubiquitous, location-based social networking websites (e.g., Gowalla, BrightKite, Foursquare) are getting more and more popular. Along with location-based social networking services being prominent, new kind of data came into play besides the traditional social networking data: (1) Spatial data: represents the users geo-locations, venues geo-locations and information about users visiting different venues. (2) Users Opinions data: represents how much a user likes the venues she visits (e.g., Alice visited restaurant A and gave it a rating of five over five). In this paper, we present PLUTUS, a framework that assists venues (e.g., restaurant, gym, shopping mall) owners in growing their business. To recommend the best set of customers, PLUTUS takes three main aspects into consideration: (1) Social aspect, (2) Spatial aspect, and (3) Users opinions aspect. To this end, PLUTUS proposes two main algorithms: (1) Profit Calculation: It is responsible of calculating the total profit that a user u may add to a venue v taking into account the social, spatial, and user opinions aspects. (2) Profit Maximization: This algorithm is used to maximize the total profit of a given venue. We evaluated PLUTUS using real data set extracted from an existing Location-based Social Networking website, Foursquare. The results show that Plutus achieves higher estimated profit and more efficient profit calculation than naive marketing algorithms.

Original languageEnglish (US)
Article number6569119
Pages (from-to)26-35
Number of pages10
JournalProceedings - IEEE International Conference on Mobile Data Management
Volume1
DOIs
StatePublished - Sep 11 2013
Event14th International Conference on Mobile Data Management, MDM 2013 - Milan, Italy
Duration: Jun 3 2013Jun 6 2013

Keywords

  • Data
  • Graph
  • Location
  • Mobile
  • Opinion
  • Profit
  • Rating
  • Recommend
  • Social
  • Spatial
  • Temporal

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