A novel approach for mining cyclically repeated patterns with multiple minimum supports

被引:8
|
作者
Hu, Ya-Han [1 ]
Tsai, Chih-Fong [2 ]
Tai, Chun-Tien [1 ,3 ]
Chiang, In-Chi [1 ]
机构
[1] Natl Chung Cheng Univ, Dept Informat & Management, Chiayi 62102, Taiwan
[2] Natl Cent Univ, Dept Informat & Management, Jhongli 32001, Taiwan
[3] Chiayi Chang Gung Mem Hosp, Chiayi 61363, Taiwan
关键词
Data mining; Cyclically repeated pattern (CRP) mining Multiple minimum supports; Sequential pattern; GENERALIZED ASSOCIATION RULES; SEQUENTIAL PATTERNS; ALGORITHM;
D O I
10.1016/j.asoc.2014.10.047
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Periodic patterns and cyclic patterns have been used to discover recurring patterns in sequence databases. Toroslu (2003) proposed cyclically repeated pattern (CRP) mining, in which a new parameter called repetition support is considered in the mining process. In a data sequence, the occurrence of a subsequence must satisfy a single user-specified minimum repetition support. However, in real-life applications, items may occur at various frequencies in a database. The rare item problem may occur when all items are set to a single minimum repetition support. To solve this problem, we included the concept of multiple minimum supports to enable users to specify the multiple minimum item repetition support (MIR) according to the natures of items. In this paper, we first redefined CRPs based on the MIR and original form of the sequence minimum support. A new algorithm, rep-PrefixSpan, was developed for discovering a complete set of CRPs in sequence databases. The experimental results indicate that the proposed approach exhibits performance superior to that of conventional CRP mining. The proposed method can be applied in many application domains including customer purchase behavior, web logging, and stock analyses. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:90 / 99
页数:10
相关论文
共 50 条
  • [1] Mining of frequent patterns with multiple minimum supports
    Gan, Wensheng
    Lin, Jerry Chun-Wei
    Fournier-Viger, Philippe
    Chao, Han-Chieh
    Zhan, Justin
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2017, 60 : 83 - 96
  • [2] Partial Periodic Patterns Mining with Multiple Minimum Supports
    Yang, Kung-Jiuan
    Hong, Tzung-Pei
    Lan, Guo-Cheng
    Chen, Yuh-Min
    [J]. 2013 9TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATIONS AND SIGNAL PROCESSING (ICICS), 2013,
  • [3] Mining Frequent Patterns with Multiple Minimum Supports using Basic Apriori
    Xu, Tiantian
    Dong, Xiangjun
    [J]. 2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2013, : 957 - 961
  • [4] More Efficient Algorithm for Mining Frequent Patterns with Multiple Minimum Supports
    Gan, Wensheng
    Lin, Jerry Chun-Wei
    Fournier-Viger, Philippe
    Chao, Han-Chieh
    [J]. WEB-AGE INFORMATION MANAGEMENT, PT I, 2016, 9658 : 3 - 16
  • [5] A genetic-fuzzy mining approach for items with multiple minimum supports
    Chun-Hao Chen
    Tzung-Pei Hong
    Vincent S. Tseng
    Chang-Shing Lee
    [J]. Soft Computing, 2009, 13 : 521 - 533
  • [6] A genetic-fuzzy mining approach for items with multiple minimum supports
    Chen, Chun-Hao
    Hong, Tzung-Pei
    Tseng, Vincent S.
    Lee, Chang-Shing
    [J]. SOFT COMPUTING, 2009, 13 (05) : 521 - 533
  • [7] A genetic-fuzzy mining approach for items with multiple minimum supports
    Chen, Chun-Hao
    Hong, Tzung-Pei
    Tseng, Vincent S.
    Lee, Chang-Shing
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4, 2007, : 1738 - +
  • [8] An Asynchronous Periodic Sequential Patterns Mining Algorithm with Multiple Minimum item Supports
    Yu, Xiangzhan
    Yu, Haining
    [J]. 2014 NINTH INTERNATIONAL CONFERENCE ON P2P, PARALLEL, GRID, CLOUD AND INTERNET COMPUTING (3PGCIC), 2014, : 274 - 281
  • [9] An efficient tree-based algorithm for mining sequential patterns with multiple minimum supports
    Hu, Ya-Han
    Wu, Fan
    Liao, Yi-Jiun
    [J]. JOURNAL OF SYSTEMS AND SOFTWARE, 2013, 86 (05) : 1224 - 1238
  • [10] Constraint Programming for Itemset Mining with Multiple Minimum Supports
    Belaid, Mohamed-Bachir
    Lazaar, Nadjib
    [J]. 2021 IEEE 33RD INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2021), 2021, : 598 - 603