Volume 10 Number 10 (Oct. 2015)
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JSW 2015 Vol.10(10): 1228-1234 ISSN: 1796-217X
doi: 10.17706/jsw.10.10.1228-1234

A Web Log Frequent Sequential Pattern Mining Algorithm Linked WAP-Tree

Zhengyu Zhu1, Meiyu Zheng1*, Yihan Wu2
1 College of Computer Science, Chongqing University, Chongqing 400030, China.
2Beijing Normal University, Beijing 100000, China.



Abstract—Web log frequent sequence pattern mining is an important field of Web log mining and of discovering interactive frequent sequence pattern between users and websites. It is easy to analyse users’ access sequence patterns by utilizing these sequence patterns and it is meaningful to build an intelligent website by mining Web log frequent sequential patterns. The PREWAP algorithm proposed in the paper makes full use of creating descendant of new node while constructing its WAP-tree and results in the serial number of pre-visiting while constructing its header table to judge the relationship of all nodes. The experiments show that mining web log using the PREWAP algorithm is much more efficient than using the current PLWAP, NGCWAP and WAP algorithms, especially on memory consumption.

Index Terms—Data mining, web log, frequent pattern, sequential pattern; WAP-tree.

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Cite: Zhengyu Zhu, Meiyu Zheng, Yihan Wu, "A Web Log Frequent Sequential Pattern Mining Algorithm Linked WAP-Tree," Journal of Software vol. 10, no. 10, pp. 1228-1234, 2015.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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