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논문검색

Novel Algorithms for Asynchronous Periodic Pattern Mining Based on 2-D Linked List

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

저자정보

  • Jieh-Shan Yeh Department of Computer Science and Information Management, Providence University, Taiwan
  • 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

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