Predicting next page access by time length reference in the scope of effective use of resources

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. The system keeps all user information and uses this information to recognize the other user visiting the web site. 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. Here, “parent domain” identifies the domain in which the identity belongs to. For instance, “bilkent.edu.tr” is the parent domain of the “cs.bilkent.edu.tr”. The importance of the pages that the visitors are really interested in and the identity information forms the skeleton of the system. The assumption that the amount of time a user spends on iv page correlates to whether the page should be classified as a navigation or content page for that user. The other criterion, the identity information, is another important point of the thesis. In case of having no recommendation according to the past experiences of the visitor, the identity information is located into appropriate parent domain or class to get other recommendation according to the interests of the visitors coming from its parent domain or class because we assume that the visitors from the same domain will have similar interests. 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 have been used in our system in the scope of “Efficient Use of the Resources” concept. We have tested the system on the web site of CS Department of Bilkent University. The results of the experiments have shown the efficiency and applicability of the system.