Abstract:
Web usage mining is the discovery of user
access patterns from Web usage logs. The paper
presents two XML (Extensible Markup Language) 1.0
applications and a web data mining application
which utilizes it to extract web data from web log
files. The two XML 1.0 applications are: LOGML
(Log Markup Language) is a web-log report
description language and XGMML (Extensible
Graph Markup and Modeling Language) is a graph
description language. As a case study, the system
implements a sample website for web graph
information and usage information. The main goal of
this paper is that web graph information transforms
to XGMML document and then this graph
information and cleaned usage information of
finished user sessions transforms to LOGML
document. The next goal is that these cleaned data
with LOGML document are mined with CHARM
(Closed Association Rule Mining) algorithm to
implement the most frequently accessed pages from
one site. CHARM is an efficient algorithm for mining
all closed frequent itemsets (set of all subsets of
items).
