Mining multivariate spatiotemporal patterns from heterogeneous mobility data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Mobility data mining in the form of trajectory data mining has been extensively investigated in recent years. Predictive modeling and pattern discovery approaches have been proposed to predict movements and locations, and to extract useful trajectory and location patterns. Nowadays, mobility data consist of not only trajectory data. Mobility data from smart phones include measurements such as call duration/time, call type, digital media consumption, calendar information, apps usage, social interactions, and mobile browsing. These heterogeneous multivariate data allow one to discover interesting and more complex behavioral patterns and rules in terms of space and time. In this paper, we investigate spatiotemporal rule mining on heterogeneous multivariate mobility data. We propose a systematic approach consisting of three main steps: data fusion, frequent temporal multivariate-location extraction, and rule generation. In particular, we explore the task of extracting multivariate spatiotemporal patterns corresponding to the "where", "when", and "who" queries (and their combinations) related to phone call variables collected from smart phone users. Experimental results on the data from Nokia Mobile Data Challenge is used to show the feasibility and usefulness of our proposed approach.

Original languageEnglish (US)
Title of host publication20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012
Pages486-489
Number of pages4
DOIs
StatePublished - Dec 1 2012
Event20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012 - Redondo Beach, CA, United States
Duration: Nov 6 2012Nov 9 2012

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Other

Other20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012
CountryUnited States
CityRedondo Beach, CA
Period11/6/1211/9/12

All Science Journal Classification (ASJC) codes

  • Earth-Surface Processes
  • Computer Science Applications
  • Modeling and Simulation
  • Computer Graphics and Computer-Aided Design
  • Information Systems

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