Mining web logs for prediction models in WWW caching and prefetching
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Using Markov models for web site link prediction
Proceedings of the thirteenth ACM conference on Hypertext and hypermedia
Prediction of Web Page Accesses by Proxy Server Log
World Wide Web
Unraveling the Web Services Web: An Introduction to SOAP, WSDL, and UDDI
IEEE Internet Computing
Identifying Interesting Customers through Web Log Classification
IEEE Intelligent Systems
Mining longest repeating subsequences to predict world wide web surfing
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
Hi-index | 0.00 |
Information of network grows up fast, and there is an important thing providing user a tool which could search information quickly. In order to achieve this purpose and we must track and analyze user behavior of network. We apply data mining approach which is used to accurately capture user behavior of network traffic, and the proposed prediction model is constructed by log database. This research is used Petri-net method to grasp the user behavior accurately, and it offers path of user behavior. And we use converted weight matrix method to construct rule table and prediction model, and it has flexibility to make management and access of the database more convenient. The experimental results showed that improve site of website and predict path of user behavior efficiently.