Abstract—Application of data mining technique to the World
Wide Web refers to as Web mining. Web based origination
collects large volume of data for their operation. Analysis of
such data can help the organization for better working
(Marketing strategy, services, evaluation of effectiveness,
promotional campaigns etc). This type of analysis require
discovery of meaningful relationships from the large collection
of primarily unstructured data stored in Web server access logs.
We propose a new approach for automatically learning
(context-free) grammar rules form server access log text
(positive set) samples, based on the alignments between the
sentences. Our approach works on pairs of unstructured
sentences that have one or more words common.
Index Terms—Web usage mining, computational learning,
grammatical inference, alignment profile, information
extraction.
Ramesh Thakur is with the International Institute of Professional Studies,
Devi Ahilya University, and Indore, India (e-mail:
r_thakur@rediffmail.com).
Suresh Jain is with the KCB Technical Academy, Indore, India (e-mail:
suresh.jain@rediffmail.com).
Narendra S.Chaudhari is with the Indian Institute of Technology, Indore,
India (e-mail: nsc183@gmail.com).
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Cite:Ramesh Thakur, Suresh Jain, and Narendra S. Chaudhari, "User Behavior Analysis Using Alignment Based
Grammatical Inference from Web Server Access Log," International Journal of Future Computer and Communication vol. 2, no. 6, pp. 543-547, 2013.
