Mining Frequent Trajectory Patterns in Spatial-temporal Databases
Date Issued
2007
Date
2007
Author(s)
Ip, Weng Chong
DOI
en-US
Abstract
With advances in tracking technologies and great diffusion of location-based services, a large amount of data has been collected in a spatial-temporal database. The implicit knowledge in a spatial-temporal database can be used in many application areas and mining frequent trajectories in the spatial-temporal database can help us understand the movements of objects. Therefore, in this thesis, we propose a novel algorithm to mine the frequent trajectory patterns in a spatial-temporal database. Our proposed method consists of two phases. First, we transform all trajectories in the database into a mapping graph. For each vertex in the mapping graph, we record the information of the trajectories passing through the vertex in a data structure, called Trajectories Information lists (TI-lists). Second, we mine all frequent patterns from the mapping graph and TI-lists in a depth-first search manner. Our proposed method doesn’t generate unnecessary candidates, needs fewer database scans, and utilizes the consecutive property of trajectories to reduce the search space. Therefore, our proposed method is more efficient than the PrefixSpan-based method. The experiment results show that our proposed method outperforms PrefixSpan-based method by one order of magnitude in synthetic data and real data.
Subjects
資料探勘
時空資料庫
時空樣式
頻繁路徑
演算法
data mining
spatial-temporal databases
spatial-temporal patterns
frequent trajectories
algorithm
Type
other
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