A01=K. S. Oza
A01=R.K. Kamat
A01=V.S. Kumbhar
Age Group_Uncategorized
Age Group_Uncategorized
Author_K. S. Oza
Author_R.K. Kamat
Author_V.S. Kumbhar
automatic-update
Category1=Non-Fiction
Category=UMW
Category=UNF
Classification Algorithms
commercial website evaluation
Commercial Websites
COP=Denmark
CSS File
Data Mining
Data Mining Algorithms
Data Mining Methods
Data Mining Systems
data mining techniques
Data Preprocessing Techniques
Delivery_Pre-order
Distributed Data Mining
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
GKD
Image Caching
J48 Algorithm
KDD Process
Keyword Density
Language_English
machine learning algorithms
PA=Not yet available
Page Caching
Price_€20 to €50
PS=Forthcoming
RBF Network
SEO performance metrics
Site Analyzer Tool
SMO Algorithm
softlaunch
URL Rewrite
Web Content Mining
Web Data Mining
Web Mining
Web Structure Mining
Web Usage Mining
website classification clustering methods
website usability analysis
WEKA data processing
Product details
- ISBN 9788770044516
- Weight: 400g
- Dimensions: 156 x 234mm
- Publication Date: 21 Oct 2024
- Publisher: River Publishers
- Publication City/Country: DK
- Product Form: Paperback
- Language: English
Secure
checkout
Fast Shipping
Easy returns
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 miningBusiness websites domain researched, and data collected using site-analyzer toolAccessibility, design, text, multimedia, and networking are assessedDatasets are filtered further by selecting vital attributes which are Search Engine Optimized for processing using the Weka attributed toolDataset with labels have been classified using J48, RBFNetwork, NaïveBayes, and SMO techniques using WekaA comparative analysis of all classifiers is reportedCommercial applications for improving website performance based on SEO is given
V.S. Kumbhar, K. S. Oza, R.K. Kamat
