A WEB PERSONALIZATION BASED ON THE SEQUENTIAL PATTERN MINING FOR IMPROVED WEB ACCESS

Abstract
The development of information technology, the web has created a big challenge for directing the client to the website pages according to their need. Web page personalization process user’s query and retrieve the search results that corresponds to their interest. Accordingly, the option is to capture the intuition of the client and provide them a list of recommendation. The tedious work is, to find the user’s intuition. The web master of an institution ought to utilize methods of web mining to fetch the user’s intuition. The web usage mining is one the technique to find the users intuition. Web usage mining can provide patterns of usage to the organizations in order to obtain user profiles and therefore they can make easier the website browsing or present specific pages. The recommendation is one of the applications in web usage mining. Recommender systems area unit one of the most common and easily apprehensible applications. There square measure 2 major ways in which most of advice engines work. They can either rely on the properties of the things that every user likes, discovering what else the user might like. In this paper, we tend to propose a recommendation approach that recommends a number of web pages based on user’s interest upon client’s history, from the web log. In this approach, it brings the most accuracy of the web pages to be displayed for the user.

Authors
A Vaishnavi, N Balakumar
Pioneer College of Arts and Science, India

Keywords
Web Usage Mining, Recommendation, Web Personalization, Web Log, Sequential Pattern Mining, Web Mining
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 9 , Issue: 3 )
Date of Publication :
April 2019
DOI :

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