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Semantic trajectory mining for location prediction

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Published:01 November 2011Publication History

ABSTRACT

Research on predicting movements of mobile users has attracted a lot of attentions in recent years. Many of those prediction techniques are developed based only on geographic features of mobile users' trajectories. In this paper, we propose a novel approach for predicting the next location of a user's movement based on both the geographic and semantic features of users' trajectories. The core idea of our prediction model is based on a novel cluster-based prediction strategy which evaluates the next location of a mobile user based on the frequent behaviors of similar users in the same cluster determined by analyzing users' common behavior in semantic trajectories. Through a comprehensive evaluation by experiments, our proposal is shown to deliver excellent performance.

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          cover image ACM Conferences
          GIS '11: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
          November 2011
          559 pages
          ISBN:9781450310314
          DOI:10.1145/2093973

          Copyright © 2011 ACM

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 1 November 2011

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          Overall Acceptance Rate220of1,116submissions,20%

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