Selecting Clickstream Data Mining Plans Using A
Case-based Reasoning Application
Author(s)
C. Wanzeller & O. Belo
Abstract
Despite the increasing interest and wide use of data mining tools, extracting
useful knowledge from the growing available data remains a complex task. The
Web environment and clickstream data demand even more efficacy to
knowledge discovery: such data is a rich, complex and huge source of
information; the discoveries are easily actionable; and time constrains are
typically hard. One general, crucial and very challenge issue of knowledge
discovery is the selection of the right methods to apply according to the nature of
the problem under analysis. This issue, particularly within the Web usage mining
scope, is the focus of our work. This paper describes a case-based reasoning
system especially oriented to assist users in the development and application of
Web usage mining processes. This system takes as inputs the characteristics of
the available data, the analysis’ requirements, and, based on acquired experience
from successfully processes, delivers a solution: a mining plan suited to the data
analysis problem at hand.
Keywords: Web usage mining, case based reasoning, clickstream analysis, data
mining assistance and data mining plans selection.
1 Introduction
Today, organizations are adapting their way of being in the electronic commerce
arena. Some of them try hard to know how users act when visiting the sites they
promote and sustain. Basically, they intend to gather information about the
impact and effectiveness of their sites without questioning directly users. Regular
Keywords
Web usage mining, case based reasoning, clickstream analysis, data
mining assistance and data mining plans selection.
Related Book
Other papers in this volume
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