JACIII Vol.23 No.5 pp. 956-961
doi: 10.20965/jaciii.2019.p0956


A Parallel Algorithm for Mining Non-Redundant Recurrent Rules from a Sequence Database

Seung-Yong Yoon and Hirohisa Seki

Department of Computer Science, Nagoya Institute of Technology
Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan

February 20, 2018
May 30, 2019
September 20, 2019
data mining, sequential rule, recurrent rule, sequence database, parallel algorithm

We propose a parallel algorithm for mining non-redundant recurrent rules from a sequence database. Recurrent rules, proposed by Lo et al. [1], can express “Whenever a series of precedent events occurs, eventually a series of consequent events occurs,” and they have shown the usefulness of recurrent rules in various domains, including software specification and verification. Although some algorithms such as NR3 have been proposed, mining non-redundant recurrent rules still requires considerable processing time. To reduce the computation cost, we present a parallel approach to mining non-redundant recurrent rules, which fully utilizes the task-parallelism in NR3. We also give some experimental results, which show the effectiveness of our proposed method.

Cite this article as:
S. Yoon and H. Seki, “A Parallel Algorithm for Mining Non-Redundant Recurrent Rules from a Sequence Database,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.5, pp. 956-961, 2019.
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Last updated on Nov. 18, 2019