Sequential Pattern Discovery method for Pattern classification in web usage Mining

Abstract

The arrival of novel technologies in our daily lives has been much emphasised compare to last decade. This has led to a multiplication of data mining tools aimed at obtaining knowledge from these data sources.Novel approach to classifying user navigation patterns and predicting users’ future requests. The approach is based on the combined mining of web server logs and the contents of the retrieved web pages. The textual content of web pages is captured through extraction of characterN-grams, which are combined with Web server log files toderive user navigation profiles. The approach is implemented as an experimental system, and its performance is evaluated based on two tasks names as classification and prediction. This approach may be used to facilitatebetter web personalization and website organization. Pattern discovery from web page navigation sequences involves application of data mining and pattern classification methods to discover the patterns have subsequently accessed interesting page categories and user groups. In this paper, the proposed SPDM helps to discovering sequential patterns from web page navigation.