A Spatial Clustering Approach by Combining the Geo-Social-Comment Relationships of POIs

摘要：

　　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.

关键词： Spatial Clustering Geo-Social-Comment(GSC)Relation Model Density-based Clustering Adjacency List Index

作者: Xiaoyan Zhang Yue Mao Xiangfu Meng

作者单位: School of Electronic and Information Engineering Liaoning Technical University Huludao 125105,China

会议类型: 国际会议

会议名称: 2019国图灵大会(ACM Turing Celebration conference-China 2019 )

会议地点: 成都

会议语种:英文

页码: 35-39

在线出版日期: 2019-05-17（万方平台首次上网日期，不代表论文的发表时间）