Abstract—Web usage mining (WUM) is one of the categories
of data mining technique that identifies usage patterns of the
web data, so as to perceive and better serve the requirements of
the web applications. The working of WUM involves three steps
– preprocessing, pattern discovery and analysis. The first step
in WUM - Preprocessing of data is an essential activity which
will help to improve the quality of the data and successively the
mining results. This research paper studies and presents several
data preparation techniques of access stream even before the
mining process can be started and these are used to improve the
performance of the data preprocessing to identify the unique
sessions and unique users. The methods proposed will help to
discover meaningful pattern and relationships from the access
stream of the user and these are proved to be valid and useful by
various research tests. We have concluded this paper by
proposing the future research directions.
Index Terms—Web usage mining, data preprocessing,
weblog, user session, path completion.
K. Sudheer Reddy is with the Dept. of Computer Science & Engineering
of Acharya Nagarjuna University, Guntur, AP, India (e-mail:
sudheercse@gmail.com).
G. P. Saradhi Varma is with the Dept. of Information Technology, SRKR
Engineering College, Bhimavaram, AP, India.
Kantha Reddy is with Indo US Collaboration for Engineering Education
(IUCEE), UML, Lowell, USA.
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Cite:K. Sudheer Reddy, G. Partha Saradhi Varma, and M. Kantha Reddy, "An Effective Preprocessing Method for Web Usage Mining," International Journal of Computer Theory and Engineering vol. 6, no. 5, pp. 412-415, 2014.
