Context-aware location recommendation by using a random walk-based approach

Bagci H., KARAGÖZ P.

KNOWLEDGE AND INFORMATION SYSTEMS, cilt.47, ss.241-260, 2016 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 47 Konu: 2
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1007/s10115-015-0857-0
  • Sayfa Sayıları: ss.241-260


The location-based social networks (LBSN) enable users to check in their current location and share it with other users. The accumulated check-in data can be employed for the benefit of users by providing personalized recommendations. In this paper, we propose a context-aware location recommendation system for LBSNs using a random walk approach. Our proposed approach considers the current context (i.e., current social relations, personal preferences and current location) of the user to provide personalized recommendations. We build a graph model of LBSNs for performing a random walk approach with restart. Random walk is performed to calculate the recommendation probabilities of the nodes. A list of locations are recommended to users after ordering the nodes according to the estimated probabilities. We compare our algorithm, CLoRW, with popularity-based, friend-based and expert-based baselines, user-based collaborative filtering approach and a similar work in the literature. According to experimental results, our algorithm outperforms these approaches in all of the test cases.