Abstract:
Analyzing and exploring regularities in the
behavior of the web page reader is imprinted on
the web server log files can improve system
performance; enhance the quality and delivery of
Internet information services to the end user.Web
mining techniques can use to search for web
access patterns, web structures, regularity and
dynamics of web contents. OLAP (Online
Analytical Processing)-based association rule
mining integrates OLAP and association rule
mining that facilitates flexible mining of
interesting knowledge in data cube because it can
be performed at multilevel or multidimensional in
data cube.In this system, Web log database is used
to store web log records of log files collected from
web server. And web log database are constructed
via a process of data cleaning, data
transformation. Data cube will be implemented
from log files.Generating rules from data cube
will reduce counting phase of association rule
since it stores the pre-computed count
values.Frequent patterns are generated based on
dimensions of the web logs instead of page itemsets.
The generated frequent patterns can later be
applied to improve web site management, decision
making process.
