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 the application of data mining techniques to discover usage patterns and behaviors from web data (clickstream, purchase information, customer information, etc.) in order to understand and serve e-commerce customers better and improve the online business. In this article, we present a general data warehouse/online analytic processing (OLAP) framework for web usage mining and ...

Web Mining is a challenging task that searches for Web access patterns, Web structures and the regularity and dynamics of the Web contents. It provides efficient Web Personalization, System Improvement, Site Modification, Business Intelligence and Usage Characterization. High-dimensional Web Log File clustering is a challenging task and requires an efficient clustering technique. The efficiency...

Frequent pattern mining plays a major role in mining of web log files. Web usage mining is the one of the web mining process that involves application of mining techniques to web server logs to extract the behavior of users. A web usage mining consists of three important phases: data preprocessing, patterns discovery and pattern analysis. In data preprocessing phase the unwanted data are remove...

The World Wide Web is the most wide known information source that is easily available and searchable. It consists of billions of interconnected documents Web pages are authored by millions of people. Accesses made by various users to pages are recorded inside web logs. These log files exist in various formats. Because of increase in usage of web, size of web log files is increasing at a much fa...

Web usage Mining is an area of web mining which deals with the extraction of interesting knowledge from logging information produced by web server. Different data mining techniques can be applied on web usage data to extract user access patterns and this knowledge can be used in variety of applications such as system improvement, web site modification, business intelligence etc. Web usage minin...

In recent years, e-businesses have been profiting from recent advances on the analysis of web customer behaviour. For decades experts have debated on ways of presenting the content or structure in a web site in order to captivate the attention of the web user in the web intelligence community. A solution to this could help boost sales in an e-commerce site. Web Usage Mining (WUM) is the extract...

With the rapid growth of the World Wide Web, the use of automated Web-mining techniques to discover useful and relevant information has become increasingly important. One challenging direction is Web usage mining, wherein one attempts to discover user navigation patterns of Web usage from Web access logs. Properly exploited, the information obtained from Web usage log can assist us to improve t...

We present a tool that alleviates the tedious work of data pre-processing and data structuring to support scientific research on web usage mining (WUM). Furthermore, the framework contains web usage mining models as well as methods for basic statistics on the structured data. The contribution of the tool is a tree-like visualization of frequent navigational sequences. This visualization allows ...

Web usage mining is the application of data mining techniques to discover usage patterns and behaviors from web data (clickstream, purchase information, customer information etc) in order to understand and serve e-commerce customers better and improve the online business. In this paper we present a general Data Warehouse/OLAP framework for web usage mining and business intelligence reporting. W...