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A spatial clustering approach by combining the geo-social-comment relationships of POIs

Existing spatial clustering approaches mainly consider the location distance (or/and social relationship) between spatial objects while ignore the user comment relationship between them. This paper proposes a spatial clustering method which combines the location, social, and comment relationships of spatial objects. First, the spatial object's Geographic-Social-Comment (GSC) relation model is constructed. And then, the methods for evaluating the social relationships and comment similarities between spatial objects are proposed, respectively. To improve the efficiency of the spatial clustering algorithm, a novel index structure and the corresponding implementation algorithm are also presented. The experimental results demonstrate that the spatial clustering results obtained by our method are more reasonable, the social connections and comment similarities within the cluster are more closely.