A post-processing approach to improve the accuracy in POI recommendation

• Luiz Felipe Chaves UFSJ
• Nícollas Silva UFMG
• Leonardo Rocha UFSJ

Abstract

Recommender Systems (RS) have been applied in several scenarios, such as entertainment, e-commerce, and nowadays, in Location-Based Social Network (LBSN) to recommend points-of-interest (POIs). In POIs domains, there is still an opportunity for improvements, on which it is necessary to consider the geographic influence of them. The actual main proposals are not able to achieve satisfactory results. In this work, we open a new research perspective, proposing a post-processing approach that can be used with any RS. We measure the activity level of users in different subareas of a city and use it to re-order the POIs retrieved by an RS. We evaluate our proposal considering six recommender systems and three datasets from Yelp achieving gains up to 15% of precision.

Keywords: Recommender Systems, Point of Interest

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