Access log file is like a box of treasure waiting to be exploited containing valuable information for the web usage mining system. We can convert this information hidden in the access log files into knowledge by analyzing them. Analysis of web server access data can help understand the user behavior and provide information on how to restructure a web site for increased effectiveness, thereby improving the design of this collection of resources. We designed and developed a new system in this thesis to make dynamic recommendation according to the interest of the visitors by recognizing them through the web.Because the system designed do not use cookies to recognize the visitors, the system keeps all user information and uses this information to recognize the other user visiting the web site. The system acquires either the IP address or Fully Qualified Domain Name (FQDN) of the user by a scripting language called as PHP. After the visitor is recognized, the system checks whether she/he has visited the web site before or not. If the visitor has visited the web site before, it makes recommendation according to his/her past actions. Otherwise, it makes recommendation according to the visitors coming from the parent domain. Besides, the system is designed in such a way that it uses the resources of the system efficiently. “Memory Management”, “Disk Capacity” and “Time Factor” options used in our system in the scope of “Efficient Use of the Resources” concept.