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Interesting Activities Discovery for Moving Objects Based on Collaborative Filtering

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  • Guan Yuan
  • Shixiong Xia
  • Yanmei Zhang

Abstract

With the development of location-based service, more and more moving objects can be traced, and a great deal of trajectory data can be collected. Finding and studying the interesting activities of moving objects from these data can help to learn their behavior very well. Therefore, a method of interesting activities discovery based on collaborative filtering is proposed in this paper. First, the interesting degree of the objects' activities is calculated comprehensively. Then, combined with the newly proposed hybrid collaborative filtering, similar objects can be computed and all kinds of interesting activities can be discovered. Finally, potential activities are recommended according to their similar objects. The experimental results show that the method is effective and efficient in finding objects' interesting activities.

Suggested Citation

  • Guan Yuan & Shixiong Xia & Yanmei Zhang, 2013. "Interesting Activities Discovery for Moving Objects Based on Collaborative Filtering," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-9, July.
    • Handle: RePEc:hin:jnlmpe:380871
    DOI: 10.1155/2013/380871
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