---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Web access log analysis is to analyze the patterns of web site usage and the features of user’s behavior. The proposed method constructs sessions as a Directed Acyclic Graph which contains pages with calculated weights. This will help site administ...

Web usage mining is the application of web mining to discover the useful patterns from the web in order to understand and analyze the behavior of the web users and web based applications. It is the emerging research trend for today’s researchers. It entirely deals with web log files which contain the user website access information. It is an interesting thing to analyze and understand the user ...

The arrival of the computer technology has contributed the ability to produce and store the massive amounts of data. Now the world is not confined only to manually generated files or reports, but has become a giant store where vast amounts of data are collected and exchanged daily. Web pages typically contain a large amount of information that is not part of the main content of the pages, e. g....

The increasing usage of web results the heavy communication and slow returns from web. Because of this, there is the requirement of some approaches to optimize the web resources usage. One of such approach is caching that can be used within an organization to optimize the access of frequently used web pages. Caching is about to predict the requirement of next web access of a user and load it in...

A presently internet is most imperative part of human life. The internet is growing day by day, so online users are also escalating. The interesting information for knowledge of extracting from such enormous data demands for new logic and the new method. Every user spends their most of the time on the internet and their behavior is different from one and another. The application of data mining ...

Web usage mining is to discover useful patterns in the web usage data, and the patterns provide useful information about the user’s browsing behavior. This chapter examines different types of web usage traversal patterns and the related techniques used to uncover them, including Association Rules, Sequential Patterns, Frequent Episodes, Maximal Frequent Forward Sequences, and Maximal Frequent S...

In this thesis we propose a novel framework that combines Web personalization and Web directories, which results in the concept of Community Web Directories. Community Web directories is a novel form of personalization performed on Web directories, that correspond to “segments” of the directory hierarchy, representing the interests and preferences of user communities. The proposed approach is b...

Web Usage Mining (WUM) integrates the techniques of two popular research fields Data Mining and the Internet. By analyzing the potential rules hidden in web logs, WUM helps personalize the delivery of web content and improve web design, customer satisfaction and user navigation through pre-fetching and caching. This paper introduces two prevalent data mining algorithms FPgrowth and PrefixSpan i...

Web usage mining is a type of web mining, which exploits data mining techniques to extract required information from navigational behaviour of WWW users. Hence the data must be preprocessed to improve the efficiency and ease of the mining process. So it is important to pre-process before applying data mining techniques to discover user access patterns from web logs. The main task of data pre-pr...

Clustering web users is one of the most important research topics in web usage mining. Existing approaches cluster web users based on the snapshots of web user sessions. They do not take into account the dynamic nature of web usage data. In this paper, we focus on discovering novel knowledge by clustering web users based on the evolutions of their historical web sessions. We present an algorith...