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A novel algorithm for mining closed temporal patterns from interval-based data

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Abstract

Closed sequential patterns have attracted researchers’ attention due to their capability of using compact results to preserve the same expressive power as conventional sequential patterns. However, studies to date have mainly focused on mining conventional patterns from time interval-based data, where each datum persists for a period of time. Few research efforts have elaborated on discovering closed interval-based sequential patterns (also referred to as closed temporal patterns). Mining closed temporal patterns are an arduous problem since the pairwise relationships between two interval-based events are intrinsically complex. In this paper, we develop an efficient algorithm, CCMiner, which stands for Closed Coincidence Miner to discover frequent closed patterns from interval-based data. The algorithm also employs some optimization techniques to effectively reduce the search space. The experimental results on both synthetic and real datasets indicate that CCMiner not only significantly outperforms the prior interval-based mining algorithms in execution time but also possesses graceful scalability. Furthermore, we also apply CCMiner to a real dataset to show the practicability of time interval-based closed pattern mining.

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Acknowledgments

Yi-Cheng Chen was supported by the Ministry of Science and Technology, Project No. 103-2218-E-032 -003. Julia Tzu-Ya Weng was supported by the Ministry of Science and Technology under Project No. 103-2221-E-155-038.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, Tamkang University, New Taipei City, Taiwan

    Yi-Cheng Chen

  2. Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan

    Julia Tzu-Ya Weng

  3. Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan

    Julia Tzu-Ya Weng

  4. Department of Innovative Information and Technology, Tamkang University, New Taipei City, Taiwan

    Lin Hui

Authors
  1. Yi-Cheng Chen
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  2. Julia Tzu-Ya Weng
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  3. Lin Hui
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Correspondence to Yi-Cheng Chen.

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Chen, YC., Weng, J.TY. & Hui, L. A novel algorithm for mining closed temporal patterns from interval-based data. Knowl Inf Syst 46, 151–183 (2016). https://doi.org/10.1007/s10115-014-0815-2

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  • DOI: https://doi.org/10.1007/s10115-014-0815-2

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