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Books > Computing & IT > Computer programming
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Web Mining - A Synergic Approach Resorting to Classifications and Clustering (Hardcover)
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Web Mining - A Synergic Approach Resorting to Classifications and Clustering (Hardcover)
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Web mining is the application of data mining strategies to excerpt
learning from web information, i.e. web content, web structure, and
web usage data. With the emergence of the web as the predominant
and converging platform for communication, business and scholastic
information dissemination, especially in the last five years, there
are ever increasing research groups working on different aspects of
web mining mainly in three directions. These are: mining of web
content, web structure and web usage. In this context there are
good number of frameworks and benchmarks related to the metrics of
the websites which is certainly weighty for B2B, B2C and in general
in any e-commerce paradigm. Owing to the popularity of this topic
there are few books in the market, dealing more on such performance
metrics and other related issues. This book, however, omits all
such routine topics and lays more emphasis on the classification
and clustering aspects of the websites in order to come out with
the true perception of the websites in light of its usability. In
nutshell, Web Mining: A Synergic Approach Resorting to
Classifications and Clustering showcases an effective methodology
for classification and clustering of web sites from their usability
point of view. While the clustering and classification is
accomplished by using an open source tool WEKA, the basic dataset
for the selected websites has been emanated by using a free tool
site-analyzer. As a case study, several commercial websites have
been analyzed. The dataset preparation using site-analyzer and
classification through WEKA by embedding different algorithms is
one of the unique selling points of this book. This text projects a
complete spectrum of web mining from its very inception through
data mining and takes the reader up to the application level.
Salient features of the book include: - Literature review of
research work in the area of web mining - Business websites domain
researched, and data collected using site-analyzer tool -
Accessibility, design, text, multimedia, and networking are
assessed - Datasets are filtered further by selecting vital
attributes which are Search Engine Optimized for processing using
the Weka attributed tool - Dataset with labels have been classified
using J48, RBFNetwork, NaiveBayes, and SMO techniques using Weka -
A comparative analysis of all classifiers is reported - Commercial
applications for improving website performance based on SEO is
given
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