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EDBT
2006
ACM

TrajPattern: Mining Sequential Patterns from Imprecise Trajectories of Mobile Objects

12 years 5 months ago
TrajPattern: Mining Sequential Patterns from Imprecise Trajectories of Mobile Objects
Abstract. Mobile objects have become ubiquitous in our everyday lives, ranging from cellular phones to sensors, therefore, analyzing and mining mobile data becomes an interesting problem with great practical importance. For instance, by finding trajectory patterns of the mobile clients, the mobile communication network can allocate resources more efficiently. However, due to the limited power of the mobile devices, we are only able to obtain the imprecise location of a mobile object at a given time. Sequential patterns are a popular data mining model. By applying the sequential pattern model on the set of imprecise trajectories of the mobile objects, we may uncover important information or further our understanding of the inherent characteristics of the mobile objects, e.g., constructing a classifier based on the discovered patterns or using the patterns to improve the accuracy of location prediction. Since the input data is highly imprecise, it may not be possible to directly apply an...
Jiong Yang, Meng Hu
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2006
Where EDBT
Authors Jiong Yang, Meng Hu
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