Authors

1. Ms. Khushboo Saxena
2. Dr. Akash Saxena

Affiliation

• Asst. Porofessor Corporate Institute of Science and Technology, Bhopal
• Associate Professor Compucom Institute of IT & Management, Jaipur

Abstract

In an era of technology, human collects huge amount of structural and unstructured data, in this scenario World Wide Web (WWW) performs vital role to find the solution in a single place. Various implementers give different types of data model to implement this. Web mining can be understand by three ways i.e. web structure mining, web usage mining, and web content mining. This paper focus on web usage mining, aims to describe pre-fetching system, extract useful information among huge amount of data, define user’s navigation, customer future prediction on the basis of navigation, Web personalization, web caching.
Various work of web usage mining has been proposed based on their threshold, time taken, and error rate; so in this paper, we proposed an integrated efficient web usage mining algorithm using fuzzy clustering and genetic algorithm which is able to generate better results as compared to previous results.

Keywords

World Wide Web (WWW), , Fuzzy Clustering, , Genetic algorithm, Web Usage Mining

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