Earticle

초록

영어

Periodic pattern mining has gained a great attention in the past decade. Previous studies mostly focus on synchronous periodic patterns. The literature proposes many methods for mining periodic patterns. Nevertheless, asynchronous periodic pattern mining has gradually received more attention recently. In this paper, we propose an efficient 2-D linked structure and the OEOP (One Event One Pattern) algorithm to discover all kinds of valid segments in each single event sequence. Then, referring to the general model of asynchronous periodic pattern mining proposed by Huang and Chang, this study combines these valid segments found by OEOP into 1-patterns with multiple events, multiple patterns with multiple events and asynchronous periodic patterns. The experimental results show that these algorithms have good performance and scalability.

목차

Abstract
 1. Introduction
 2. Problem Definition
 3. Proposed Data Structures and Algorithms
  3.1 OEOP (One Event One Pattern Mining) Algorithm
  3.2 MEOP and MEMP Algorithms
  3.3 APP Algorithm
 4. Experimental Results
  4.1 Datasets
  4.2 Numbers of valid segments and sub-sequences
  4.3 OEOP Results
  4.3 MEOP and MEMP Results
 5. Conclusions
 Acknowledgments
 References

키워드

저자

• Jieh-Shan Yeh [ Department of Computer Science and Information Management, Providence University, Taiwan ] Corresponding Author
• Szu-Chen Lin [ Department of Computer Science and Information Management, Providence University, Taiwan ]
• Shueh-Cheng Hu [ Department of Computer Science and Communication Engineering, Providence University, Taiwan ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605