A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites

A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites

Abstract

      This paper provides a complete framework and findings in mining Web usage patterns from Web log files of a real Web site that has all the challenging aspects of real-life Web usage mining, including evolving user profiles and external data describing an ontology of the Web content.  

      Hence, we present an approach for discovering and tracking evolving user profiles.

      Profiles are also enriched with other domain-specific information facets that give a panoramic view of the discovered mass usage modes.

      An objective validation strategy is also used to assess the quality of the mined profiles, in particular their adaptability in the face of evolving user behavior.

Existing System

      There was no system presenting a fully integrated approach to mine a real Web site with the challenging characteristics of today’s Web sites, such as evolving profiles, dynamic content, and the availability of taxonomy or databases in addition to Web logs.

Proposed System

      Here we present a complete framework for mining Web usage patterns with real-world challenges such as evolving access patterns, dynamic pages, and external data describing an ontology of the Web content and how it relates to the business actors

      The Web site in this study is a portal that provides access to news, events, resources, company information and a library.

      The Web site in our study is managed by a nonprofit organization that does not sell anything but only provides free information.

      Here we perform clustering of the user sessions extracted from the Web logs to partition the users into several homogeneous groups with similar activities and then extract user profiles from each cluster as a set of relevant URLs.

      Data mining techniques have been applied to extract usage patterns from Web log data, this process is known as Web usage mining.

      Several stages are:

d Collection of Web data such as activities/click streams recorded in Web server logs

d Preprocessing of Web data such as identifying unique sessions

d Analysis of Web data  to discover interesting usage patterns or profiles

d Interpretation/evaluation of the discovered profiles.

d tracking the evolution of the discovered profiles

Conclusion

      Here, we presented a framework for mining, tracking, and validating evolving multifaceted user profiles on Web sites that have all the challenging aspects of real-life Web usage mining, including evolving user profiles and access patterns, dynamic Web pages, and external data describing an ontology of the Web content.

      A multifaceted user profile summarizes a group of users with similar access activities and consists of their viewed pages, search engine queries, and inquiring and inquired companies.

SYSTEM REQUIREMENTS

Hardware Requirements

            Processor                     :           Pentium III / IV

            Hard Disk                   :           40 GB

            Ram                             :           256 MB

Monitor                       :           15VGA Color

            Mouse                         :           Ball / Optical

            Keyboard                    :           102 Keys

           

Software Requirements

Operating System       :           Windows XP professional

Front End                    :           Microsoft Visual Studio .Net 2005

Language                    :           Visual C#.Net

Back End                    :           SQL Server 2000