Using Incremental Fuzzy Clustering to Web Usage Mining

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3
Avg Bid (INR)
13888
Project Budget (INR)
₹1500 - ₹12500

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.

Skills required:
Data Mining, Engineering, Java, MySQL, SQL
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