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Title: Mining non-redundant sequential rules with dynamic bit vectors and pruning techniques
Authors: Tran, Minh-Thai
Vo, Bay
Le, Bac
Keywords: Data mining;Sequential rule;Non-redundant rule;Dynamic bit vector
Issue Date: 2016
Publisher: H. : ĐHQGHN
Abstract: Most algorithms for mining sequential rules focus on generating all sequential rules. These algorithms produce an enormous number of redundant rules, making mining inefficient in intelligent systems. In order to solve this problem, the mining of non-redundant sequential rules was recently introduced. Most algorithms for mining such rules depend on patterns obtained from existing frequent sequence mining algorithms. Several steps are required to organize the data structure of these sequences before rules can be generated. This process requires a great deal of time and memory. The present study proposes a technique for mining non-redundant sequential rules directly from sequence databases. The proposed method uses a dynamic bit vector data structure and adopts a prefix tree in the mining process. In addition, some pruning techniques are used to remove unpromising candidates early in the min-ing process. Experimental results show the efficiency of the algorithm in terms of runtime and memory usage
Description: APPLIED INTELLIGENCE Volume: 45 Issue: 2 Pages: 333-342 ; TNS06388
Appears in Collections:Bài báo của ĐHQGHN trong Web of Science

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