English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51921/87065 (60%)
Visitors : 8472803      Online Users : 89
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/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.
    Relation: IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 27(12), pp.3318-3331
    DOI: 10.1109/TKDE.2015.2454515
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML97View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback