Work

Web Access Log Mining With Soft Sequential Patterns

Year: 2006

Type: conference-paper

Abstract: 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.

Source: Applied Artificial Intelligence

DOI: 10.1142/9789812774118_0074

Authors: C. FIOT, A. LAURENT, M. TEISSEIRE

Institutions: Centre National de la Recherche Scientifique, Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier

Language: English

Topic: Data Mining Algorithms and Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2003987778

FWCI: 0.441

Cites: 11

Cited by: 3

Related to: 10