2010 | OriginalPaper | Chapter
Web Usage Mining
Authors : Pablo E. Román, Gastón L’Huillier, Juan D. Velásquez
Published in: Advanced Techniques in Web Intelligence - I
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In recent years, e-businesses have been profiting from recent advances on the analysis of web customer behaviour. For decades experts have debated on ways of presenting the content or structure in a web site in order to captivate the attention of the web user in the web intelligence community. A solution to this could help boost sales in an e-commerce site. Web Usage Mining (WUM) is the extraction of the web user browsing behaviour using data mining techniques on web data. According to this, several models of data analysis have been used to characterize the Web User Browsing Behaviour. Nevertheless, outstanding techniques have recently developed in order to improve the conventional success rates for behavioural pattern extraction. In this chapter different approaches for WUM are presented, considering their main insights, results, and applications to web behaviour systems.