Web access log mining with soft sequential patterns

被引：1

作者：

Fiot, C. ^{[1
]}

Laurent, A. ^{[1
]}

Teisseire, M. ^{[1
]}

机构：

[1] UMII, CNRS, LIRMM, Montpellier, France

来源：

APPLIED ARTIFICIAL INTELLIGENCE | 2006年

关键词：

D O I：

10.1142/9789812774118_0074

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Mining the time-stamped numerical data contained in web access logs is interesting for numerous applications (e.g. customer targeting, automatic updating of commercial websites or web server dimensioning). In this context, the algorithms for sequential patterns mining do not allow processing numerical information frequently. In previous works we defined fuzzy sequential patterns to cope with the numerical representation problem. In this paper, we apply these algorithms to web mining and assess them through experiments showing the relevancy of this work in the context of web access log mining.

引用

页码：519 / +

页数：2

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