Recognition of user browsing sequence pattern in Web log mining

Ming Xing Li; Ping Heng; Pei Wu Dong; Jian Chen

Recognition of user browsing sequence pattern in Web log mining

Ming Xing Li^*, Ping Heng, Pei Wu Dong, Jian Chen

^*Corresponding author for this work

Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

The traditional algorithm used for recognizing user browsing patterns has a fixed threshold, causing the number of the large sequence to be the opposite of the increase of sequence length. To solve this problem, an improved algorithm, IA^x algorithm is given based on the traditional association rule algorithm. The new algorithm causes the long sequence with smaller support counts to reach the threshold. Consequently, more meaningful sequence patterns can be identified and theoretically proves the validity of the new algorithm as well.

Original language	English
Pages (from-to)	1570-1572+1602
Journal	Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology
Volume	37
Issue number	11
Publication status	Published - Nov 2005
Externally published	Yes

Keywords

IA algorithm
Recognition of sequence patterns
Threshold
Web log mining

Cite this

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title = "Recognition of user browsing sequence pattern in Web log mining",

abstract = "The traditional algorithm used for recognizing user browsing patterns has a fixed threshold, causing the number of the large sequence to be the opposite of the increase of sequence length. To solve this problem, an improved algorithm, IAx algorithm is given based on the traditional association rule algorithm. The new algorithm causes the long sequence with smaller support counts to reach the threshold. Consequently, more meaningful sequence patterns can be identified and theoretically proves the validity of the new algorithm as well.",

keywords = "IA algorithm, Recognition of sequence patterns, Threshold, Web log mining",

author = "Li, {Ming Xing} and Ping Heng and Dong, {Pei Wu} and Jian Chen",

year = "2005",

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T1 - Recognition of user browsing sequence pattern in Web log mining

AU - Li, Ming Xing

AU - Heng, Ping

AU - Dong, Pei Wu

AU - Chen, Jian

PY - 2005/11

Y1 - 2005/11

N2 - The traditional algorithm used for recognizing user browsing patterns has a fixed threshold, causing the number of the large sequence to be the opposite of the increase of sequence length. To solve this problem, an improved algorithm, IAx algorithm is given based on the traditional association rule algorithm. The new algorithm causes the long sequence with smaller support counts to reach the threshold. Consequently, more meaningful sequence patterns can be identified and theoretically proves the validity of the new algorithm as well.

AB - The traditional algorithm used for recognizing user browsing patterns has a fixed threshold, causing the number of the large sequence to be the opposite of the increase of sequence length. To solve this problem, an improved algorithm, IAx algorithm is given based on the traditional association rule algorithm. The new algorithm causes the long sequence with smaller support counts to reach the threshold. Consequently, more meaningful sequence patterns can be identified and theoretically proves the validity of the new algorithm as well.

KW - IA algorithm

KW - Recognition of sequence patterns

KW - Threshold

KW - Web log mining

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M3 - Article

AN - SCOPUS:30044446365

SN - 0367-6234

VL - 37

SP - 1570-1572+1602

JO - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

JF - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

IS - 11

ER -

Recognition of user browsing sequence pattern in Web log mining

Abstract

Keywords

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