Web mining is the application of data mining techniques to extract knowledge from Web. Web mining has been explored to a vast degree and different techniques have been proposed for a variety of applications that includes Web Search, Classification and Personalization etc. The primary goal of the web site is to provide the relevant information to the users. Web mining technique is used to catego...

The Web Mining arises like an appropriate tool to exploit the derived knowledge of the web-user interaction, describing models that use patterns and characterize the profiles of the different groups of users which use Internet. To achieve this, currently there are numerous techniques. Some of these techniques are integrated in this work to build a Hybrid System of Web Mining that allows extract...

Abstract— Web mining is a class of data mining. In order to relieve a “Data Rich but Information Poor” dilemma, Data Mining emerged. Web Mining is a variation of this field that distils untapped source of abundantly available free textual information. The importance of web mining is growing along with the massive volumes of data generated in web day-to-day life. In general, web data always arri...

Nowadays, the Web is an important source of information retrieval, and the users accessing the Web are from different backgrounds. The usage information about users are recorded in web logs. Analyzing web log files to extract useful patterns is called Web Usage Mining. Web usage mining approaches include clustering, association rule mining, sequential pattern mining etc. The web usage mining ap...

Web usage mining is an application of data mining technology to mine the data of the web server log file. It can discover the browsing patterns of user and some kind of correlations between the web pages. Web usage mining provides the support for the web site design, providing personalization server and other business making decision, etc. Web mining applies the data mining, the artificial inte...

Web usage mining is the application of data mining techniques to discover usage patterns from web data. It can be used to better understand web usage and better serve the needs of rapidly growing web-based applications. Discovery of browsing patterns, page clusters, user clusters, association rules and usage statistics are some usage patterns in the web domain. Web mining of browsing patterns i...

Nowadays, the Web is an important source of information retrieval, and the users accessing the Web are from different backgrounds. The usage information about users are recorded in web logs. Analyzing web log files to extract useful patterns is called Web Usage Mining. Web usage mining approaches include clustering, association rule mining, sequential pattern mining etc. The web usage mining ap...

Utility based web access pattern mining and knowledge discovery from database has become an interesting research domain in recent time. Traditional pattern mining algorithms deal with only binary occurrence of a web page and do not consider the weight or profit of the web page. Hence, utility-based web path traversal pattern mining technique has evolved and got much interest in recent time. How...

This paper focuses on the web mining adoption of small and medium size enterprises (SMEs) in terms of organizational innovation theories. It first examines the current literature of information systems studies and suggests that the context of web mining adoption needs to be taken into account. This paper proposes an analytical model employing a number of internal, external factors, and the stag...

Semantic Web Mining can be considered as Data Mining (DM) for/from the Semantic Web. Current DM systems could serve the purpose of Semantic Web Mining if they were more compliant with, e.g., the standards of representation for ontologies and rules in the Semantic Web and/or interoperable with well-established tools for Ontological Engineering (OE) that support these standards. In this paper we ...