Data Mining: Prerequisites of Web Usage Mining - Ramya, C.;Shreedhara, K. S.
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WWW continues to grow at an overwhelming rate in both the sheer volume of traffic and the size & complexity of Web sites. Therefore, it becomes more and more necessary, but difficult to get useful information from Web data, in order to understand and better serve the needs of Web-based applications. As a result, the Web usage mining has become a hot research topic, which combines two of the prominent research areas comprising the data mining and the World Wide Web.The book gives all the details of two contributions from this research work those are preprocessing of web log data and clustering…mehr

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Produktbeschreibung
WWW continues to grow at an overwhelming rate in both the sheer volume of traffic and the size & complexity of Web sites. Therefore, it becomes more and more necessary, but difficult to get useful information from Web data, in order to understand and better serve the needs of Web-based applications. As a result, the Web usage mining has become a hot research topic, which combines two of the prominent research areas comprising the data mining and the World Wide Web.The book gives all the details of two contributions from this research work those are preprocessing of web log data and clustering of web users based on thier interest. ART1 NN algorithm is used for clustering and finally it has been proved that ART1 performs better than traditional k-means and SOM clustering algorithms.
Autorenporträt
Ramya C. & Dr.Shreedhara K.S. are presently working as lecturer & professor respectively in the department of CS&E, University B.D.T.College of Engineering, davangere, Karnataka,India. Ramya C. obtained her M.Tech degree in CS&E from Davangere University, Davangere & Dr.Shreedhara K. S. obtained his Ph.D degree from Manipal University, Karnataka.