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

^*此作品的通讯作者

Harbin Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

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.

源语言	英语
页（从-至）	1570-1572+1602
期刊	Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology
卷	37
期	11
出版状态	已出版 - 11月 2005
已对外发布	是

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Li, M. X., Heng, P., Dong, P. W., & Chen, J. (2005). Recognition of user browsing sequence pattern in Web log mining. Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 37(11), 1570-1572+1602.

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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",

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AU - Chen, Jian

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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.

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KW - Recognition of sequence patterns

KW - Threshold

KW - Web log mining

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Recognition of user browsing sequence pattern in Web log mining

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