Concurrency in Web Access Patterns Mining

Jing Lu, Malcolm Keech, Weiru Chen

Research output: Chapter in Book/Report/Published conference proceedingConference contributionpeer-review

Abstract

Web usage mining is an interesting application of data mining which provides insight into customer behaviour on the Internet. An important technique to discover user access and navigation trails is based on sequential patterns mining. One of the key challenges for web access patterns mining is tackling the problem of mining richly structured patterns. This paper proposes a novel model called Web Access Patterns Graph (WAP-Graph) to represent all of the access patterns from web mining graphically. WAP-Graph also motivates the search for new structural relation patterns, i.e. Concurrent Access Patterns (CAP), to identify and predict more complex web page requests. Corresponding CAP mining and modelling methods are proposed and shown to be effective in the search for and representation of concurrency between access patterns on the web. From experiments conducted on large-scale synthetic sequence data as well as real web access data, it is demonstrated that CAP mining provides a powerful method for structural knowledge discovery, which can be visualised through the CAP-Graph model.
Original languageEnglish
Title of host publicationInternational Conference on Data Mining, October 2009, Venice
Pages600-609
Number of pages10
Publication statusPublished - 1 Oct 2009
Externally publishedYes

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