A location-based business information recommendation algorithm

Abstract

Recently, many researches on information (e.g., POI, ADs) recommendation based on location have been done in both research and industry. In this paper, we firstly construct a region-based location graph (RLG), in which region node respectively connects with user node and business information node, and then we propose a location-based recommendation algorithm based on RLG, which can combine with user short-ranged mobility formed by daily activity and long-distance mobility formed by social network ties and sequentially can recommend local business information and long-distance business information to users. Moreover, it can combine user-based collaborative filtering with item-based collaborative filtering, and it can alleviate cold start problem which traditional recommender systems often suffer from. Empirical studies from large-scale real-world data from Yelp demonstrate that our method outperforms other methods on the aspect of recommendation accuracy.