چکیده (انگلیسی):

Websites on the internet are useful source of information in
our day-to-day activity. Web Usage Mining (WUM) is one of the major
applications of data mining, artificial intelligence and so on to the web
data to predict the user’s visiting behaviours and obtains their interests by
analyzing the patterns.WUM has turned out to be one of the considerable
areas of research in the field of computer and information science.
Weblog is one of the major sources which contain all the information
regarding the users visited links, browsing patterns, time spent on a page
or link and this information can be used in several applications like
adaptive web sites, personalized services, customer profiling, prefetching,
creating attractive web sites etc. WUM consists of
preprocessing, pattern discovery and pattern analysis. Log data is
typically noisy and unclear, so preprocessing is an essential process for
effective mining process. In the preprocessing phase, the data cleaning
process includes removal of records of graphics, videos, format
information, records with the failed HTTP status code and robots
cleaning. In the second phase, the user behaviour is organized into a set
of clusters using Weighted Fuzzy-Possibilistic C-Means (WFPCM),
which consists of “similar” data items based on the user behaviour and
navigation patterns for the use of pattern discovery. In the third phase,
classification of the user behaviour is carried out for the purpose of
analyzing the user behaviour using Adaptive Neuro-Fuzzy Inference
System with Subtractive Algorithm (ANFIS-SA). The performance of the
proposed work is evaluated based on accuracy, execution time and
convergence behaviour using anonymous microsoft web dataset.