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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/107145

    Title: Mining Temporal Patterns in Time Interval-Based Data
    Authors: Chen, Yi-Cheng;Peng, Wen-Chih;Lee, Suh-Yin
    Keywords: data mining;interval-based event;representation;sequential pattern;temporal pattern
    Date: 2016-05-16
    Issue Date: 2016-08-18 13:32:35 (UTC+8)
    Publisher: Institute of Electrical and Electronics Engineers
    Abstract: Sequential pattern mining is an important subfield in data mining. Recently, discovering patterns from interval events has attracted considerable efforts due to its widespread applications. However, due to the complex relation between two intervals, mining interval-based sequences efficiently is a challenging issue. In this paper, we develop a novel algorithm, P-TPMiner, to efficiently discover two types of interval-based sequential patterns. Some pruning techniques are proposed to further reduce the search space of the mining process. Experimental studies show that proposed algorithm is efficient and scalable. Furthermore, we apply proposed method to real datasets to demonstrate the practicability of discussed patterns.
    DOI: 10.1109/TKDE.2015.2454515
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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