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Asia-Pacific Youth Conference on Communication Technology (APYCCT 2010 E-BOOK)

Kunming,China,8.7-8.8，2010

ISBN: 978-1-935068-20-4 Scientific Research Publishing, USA

E-Book 934pp Pub. Date: August 2010

Category: Computer Science & Communications

Price: $120

Title: Research on Trajectory Clustering Algorithm Based on Reference Line
Source: Asia-Pacific Youth Conference on Communication Technology (APYCCT 2010 E-BOOK)(Part 3 Computer Technology and Application) (pp 201-207)
Author(s): Ming-tao Wang, College of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, P.R. China
De-chang Pi, College of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, P.R. China
Abstract: Existing spatial index structures can not be directly used to support efficient neighborhood query of line segment in the classic trajectory clustering algorithm TRACLUS of line segment clustering phase, which makes the time complexity of line clustering algorithm TRACLUS is O(N2), where N is the total number of line segments after trajectory partitioned phase. Therefore, it requires large volume of memory support and needs a lot of I/O costs as N increases. In this paper, reference line method is introduced to trajectory clustering to address this issue, and a novel trajectory clustering algorithm RLTC is presented in which reference line is taken into account. The main idea behind this algorithm is that a certain number of reference lines can effectively represent the spatial characteristics of a cluster region. Extensive experiments on real world datasets demonstrate that the proposed RLTC algorithm maintains the effective trajectory clustering result of TRACLUS while improves the efficiency.
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