Constraint graph-based frequent pattern updating from temporal databases

Title
Constraint graph-based frequent pattern updating from temporal databases
Author(s)
정재은
Keywords
QUERY TRANSFORMATION
Issue Date
201202
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
EXPERT SYSTEMS WITH APPLICATIONS, v.39, no.3, pp.3169 - 3173
Abstract
There have been many kinds of association rule mining (ARM) algorithms, e.g.. Apriori and FP-tree, to discover meaningful frequent patterns from a large dataset. Particularly, it is more difficult for such ARM algorithms to be applied for temporal databases which are continuously changing over time. Such algorithms are generally based on repeating time-consuming tasks, e.g., scanning databases. To deal with this problem, in this paper, we propose a constraint graph-based method for maintaining frequent patterns (FP) discovered from the temporal databases. Particularly, the constraint graph, which is represented as a set of constraint between two items, can be established by temporal persistency of the patterns. It means that some patterns can be used to build the constraint graph, when the patterns have been shown in a set of the FP. Two types of constraints can be generated by users and adaptation. Based on our scheme, we find that a large number of dataset has been efficiently reduced during mining process and the gathering information while updating. (C) 2011 Elsevier Ltd. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/29889http://dx.doi.org/10.1016/j.eswa.2011.09.003
ISSN
0957-4174
Appears in Collections:
공과대학 > 컴퓨터공학과 > Articles
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