research-article

Mining user similarity based on location history

Authors:

Wei-Ying MaAuthors Info & Claims

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

Article No.: 34, Pages 1 - 10

https://doi.org/10.1145/1463434.1463477

Published: 05 November 2008 Publication History

Abstract

The pervasiveness of location-acquisition technologies (GPS, GSM networks, etc.) enable people to conveniently log the location histories they visited with spatio-temporal data. The increasing availability of large amounts of spatio-temporal data pertaining to an individual's trajectories has given rise to a variety of geographic information systems, and also brings us opportunities and challenges to automatically discover valuable knowledge from these trajectories. In this paper, we move towards this direction and aim to geographically mine the similarity between users based on their location histories. Such user similarity is significant to individuals, communities and businesses by helping them effectively retrieve the information with high relevance. A framework, referred to as hierarchical-graph-based similarity measurement (HGSM), is proposed for geographic information systems to consistently model each individual's location history and effectively measure the similarity among users. In this framework, we take into account both the sequence property of people's movement behaviors and the hierarchy property of geographic spaces. We evaluate this framework using the GPS data collected by 65 volunteers over a period of 6 months in the real world. As a result, HGSM outperforms related similarity measures, such as the cosine similarity and Pearson similarity measures.

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Takagi SXiong LKato FCao YYoshikawa M(2024)HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data SynthesizationProceedings of the VLDB Endowment10.14778/3681954.368198317:11(3058-3071)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.14778/3681954.3681983
Amiri HYang RZüfle A(2024)GeoLife+: Large-Scale Simulated Trajectory Datasets Calibrated to the GeoLife DatasetProceedings of the 7th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation10.1145/3681770.3698573(25-28)Online publication date: 29-Oct-2024
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Index Terms

Mining user similarity based on location history
1. Computing methodologies
  1. Machine learning
2. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
    2. Retrieval tasks and goals
      1. Clustering and classification
  2. Information systems applications
    1. Data mining
      1. Clustering

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Published In

cover image ACM Conferences

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

November 2008

559 pages

ISBN:9781605583235

DOI:10.1145/1463434

Program Chairs:
Walid G. Aref
Purdue University
,
Mohamed F. Mokbel
University of Minnesota
,
Markus Schneider
University of Florida

Copyright © 2008 ACM.

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ESRI
Google Inc.
Oak Ridge National Laboratory
Microsoft: Microsoft
SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2008

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GIS '08

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Microsoft
SIGSPATIAL

GIS '08: 16th International Symposium on Advances in Geographic Information Systems

November 5 - 7, 2008

California, Irvine

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Overall Acceptance Rate 220 of 1,116 submissions, 20%

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https://doi.org/10.26599/BDMA.2023.9020029
Takagi SXiong LKato FCao YYoshikawa M(2024)HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data SynthesizationProceedings of the VLDB Endowment10.14778/3681954.368198317:11(3058-3071)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.14778/3681954.3681983
Amiri HYang RZüfle A(2024)GeoLife+: Large-Scale Simulated Trajectory Datasets Calibrated to the GeoLife DatasetProceedings of the 7th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation10.1145/3681770.3698573(25-28)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3681770.3698573
Hong ZWang HDing YWang GHe TZhang D(2024)SmallMap: Low-cost Community Road Map Sensing with Uncertain Delivery BehaviorProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36595968:2(1-26)Online publication date: 15-May-2024
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Wang HWang SLin LYang YWang SWen HSerra ESpezzano F(2024)Behavior-aware Sparse Trajectory Recovery in Last-mile Delivery with Multi-scale Attention FusionProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3680079(4931-4938)Online publication date: 21-Oct-2024
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Verma RMittal SLei ZChen XUkkusuri S(2024)Comparison of home detection algorithms using smartphone GPS dataEPJ Data Science10.1140/epjds/s13688-023-00447-w13:1Online publication date: 16-Jan-2024
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Zhao JXu JXu YFang JChao PZhou X(2024)CCML: Curriculum and Contrastive Learning Enhanced Meta-Learner for Personalized Spatial Trajectory PredictionIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.337653936:9(4499-4514)Online publication date: Sep-2024
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