Finding similar users from GPS data based on assignment problem

Zedong Lin, Q. Zeng, H. Duan, Faming Lu
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引用次数: 1

Abstract

The application of location-aware technology has increasingly accumulated a large amount of user spatiotemporal data, which gives us the opportunity to analyze users' interests and behavior patterns. This paper proposes a new method for constructing user's mobility profiles and measuring their similarity. First, a new method of using the categories of points of interest (POI) to represent the semantics of a geographical area (stay region) where a user stays for a long period of time is proposed. Second, the sequential pattern mining technique is applied to extract the user's mobility profiles. Then, the user similarity is computed based on the maximum benefit assignment problem. Finally, a comparison experiment with the existing works on the real dataset verifies the effectiveness of the proposed approach.
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基于分配问题的GPS数据查找相似用户
位置感知技术的应用越来越积累了大量的用户时空数据,这为我们分析用户的兴趣和行为模式提供了机会。本文提出了一种构造用户移动特征并度量相似性的新方法。首先,提出了一种利用兴趣点(POI)类别来表示用户停留时间较长的地理区域(停留区域)语义的新方法。其次,应用序列模式挖掘技术提取用户移动特征;然后,基于最大利益分配问题计算用户相似度。最后,在真实数据集上与已有研究成果进行了对比实验,验证了所提方法的有效性。
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