English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 95844/126434 (76%)
Visitors : 31569664      Online Users : 529
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU 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
    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/61586
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/61586

    Title: Efficient Frequent Sequence Mining by a Dynamic Strategy Switching Algorithm
    Authors: 陳良弼
    Chiu, Ding-Ying;Wu,Yi-Hung;Chen,Arbee L. P.
    Contributors: 資科系
    Keywords: Data mining;Frequent sequence;Sequence comparison;Strategy switching
    Date: 2009.01
    Issue Date: 2013-11-11 16:28:38 (UTC+8)
    Abstract: Mining frequent sequences in large databases has been an important research topic. The main challenge of mining frequent sequences is the high processing cost due to the large amount of data. In this paper, we propose a novel strategy to find all the frequent sequences without having to compute the support counts of non-frequent sequences. The previous works prune candidate sequences based on the frequent sequences with shorter lengths, while our strategy prunes candidate sequences according to the non-frequent sequences with the same lengths. As a result, our strategy can cooperate with the previous works to achieve a better performance. We then identify three major strategies used in the previous works and combine them with our strategy into an efficient algorithm. The novelty of our algorithm lies in its ability to dynamically switch from a previous strategy to our new strategy in the mining process for a better performance. Experiment results show that our algorithm outperforms the previous ones under various parameter settings.
    Relation: VLDB Journal, 18(1) , 303-327
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1007/s00778-008-0100-7
    DOI: 10.1007/s00778-008-0100-7
    Appears in Collections:[資訊科學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    303327.pdf1394KbAdobe PDF966View/Open

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

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