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Using Incremental Fuzzy Clustering to Web Usage Mining

This project was successfully completed by arsingh1212 for ₹13888 INR in 27 days.

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Project Budget
₹1500 - ₹12500 INR
Completed In
27 days
Total Bids
3
Project Description

The recent extensive growth of data on the Web,

has generated an enormous amount of log records on Web

server databases. Applying Web Usage Mining techniques

on these vast amounts of historical data can discover

potentially useful patterns and reveal user access

behaviors on the Web site. Cluster analysis has widely

been applied to generate user behavior models on Server

Web logs. Most of these off-line models have the problem

of the decrease of accuracy over time resulted of new users

joining or changes of behavior for existing users in model based approaches. This paper proposes a novel approach

to generate dynamic model from off-line model created by

fussy clustering. In this method, we will use users’

transactions periodically to change the off-line model. To

this aim, an improved model of leader clustering along

with a static approach is used to regenerate clusters in an

incremental fashion.

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