Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40948
Title: A framework for mining topological patterns in spatio-temporal databases
Authors: Wang, J. 
Hsu, W. 
Lee, M.L. 
Keywords: Data Mining
Spatio-temporal Database
Issue Date: 2005
Source: Wang, J.,Hsu, W.,Lee, M.L. (2005). A framework for mining topological patterns in spatio-temporal databases. International Conference on Information and Knowledge Management, Proceedings : 429-436. ScholarBank@NUS Repository.
Abstract: Mining topological patterns in spatial databases has received a lot of attention. However, existing work typically ignores the temporal aspect and suffers from certain efficiency problems. They are not scalable for mining topological patterns in spatio-temporal databases. In this paper, we study the problem for mining topological patterns by incorporating the temporal aspect in the mining process. We introduce a summary-structure that records the instances' count information of a feature in a region within a time window. Using this structure, we design an algorithm, TopologyMiner, to find interesting topological patterns without the need to generate candidates. Experimental results show that TopologyMiner is effective and scalable in finding topological patterns and outperforms Apriori-like algorithm by a few orders of magnitudes. Copyright 2005 ACM.
Source Title: International Conference on Information and Knowledge Management, Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/40948
ISBN: 1595931406
Appears in Collections:Staff Publications

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