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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8014

Title: Discovering during-temporal patterns (DTPs) in large temporal databases
Authors: Zhang, Li
Chen, Guoqing
BRIJS, Tom
Zhang, Xing
Issue Date: 2008
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Citation: EXPERT SYSTEMS WITH APPLICATIONS, 34(2). p. 1178-1189
Abstract: Large temporal databases (TDBs) usually contain a wealth of data about temporal events. Aimed at discovering temporal patterns with during relationship (during-temporal patterns, DTPs), which is deemed common and potentially valuable in real-world applications, this paper presents an approach to finding such DTPs by investigating some of their properties and incorporating them as desirable pruning strategies into the corresponding algorithm, so as to optimize the mining process. Results from synthetic reveal that the algorithm is efficient and linearly scalable with regard to the number of temporal events. Finally, we apply the algorithm into the weather forecast field and obtain effective results.
Notes: Tsinghua Univ, Sch Econ & Management, Beijing 100084, Peoples R China. Hasselt Univ, Transportat Res Inst, B-3920 Diepenbeek, Belgium.Chen, GQ, Tsinghua Univ, Sch Econ & Management, Beijing 100084, Peoples R China.chengq@sem.tsinghua.edu.cn
URI: http://hdl.handle.net/1942/8014
DOI: 10.1016/j.eswa.2006.12.024
ISI #: 000253238900038
ISSN: 0957-4174
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

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