الفهرس 
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Abstract
The explosive growth of the World Wide Web in recent years has turned the attention to the value of the largest source of available online data. The goal of a Web site is to meet the needs of its users. So a Web site must constantly examine its users and their use of the site, and modify itself accordingly to provide best service to them. In order to achieve that, we need to study the visitor access patterns and discover the hidden knowledge in it. Web usage mining is the approach that is concerned with mining the log files which stores visitor’s behaviors. The approach uses different data mining techniques in order to discover the hidden knowledge in these files. One of these techniques is the association rule which is a very powerful and useful one. The major drawback of it is the huge numbers of the resulted rules that make it so difficult to be analyzed. To overcome this problem we need to prune the un-useful rules and concentrate only on the meaningful ones that really reflect on the quality and strength of gained knowledge from the mining process. The study proposes a pruning technique which consists of a set of schemas tha~ success in distinguishing between the valuable associated rules and the redundant ones .The unpruned rules have proven their value III discovering the hidden knowledge from the selected web log file, III addition to forming a set of recommendations to the web master for the enhancement of the structure of the site and making user navigation as easy as possible.