GeoSoCa: Exploiting Geographical, Social and Categorical Correlations for Point-of-Interest Recommendations

@inproceedings{Zhang2015GeoSoCaEG,
  title={GeoSoCa: Exploiting Geographical, Social and Categorical Correlations for Point-of-Interest Recommendations},
  author={Jia-Dong Zhang and Chi-Yin Chow},
  booktitle={SIGIR},
  year={2015}
}
Recommending users with their preferred points-of-interest (POIs), e.g., museums and restaurants, has become an important feature for location-based social networks (LBSNs), which benefits people to explore new places and businesses to discover potential customers. However, because users only check in a few POIs in an LBSN, the user-POI check-in interaction is highly sparse, which renders a big challenge for POI recommendations. To tackle this challenge, in this study we propose a new POI… CONTINUE READING
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