Study On Web Log Mining And Applications

Web is a huge information source, but only the user, who often visits the web site, can determine whether the structure of the web site is proper. Each visit of user will register a visit log on the web server. From the web log, we can get the information, such as: URL, which the user visited, the user's IP address and the user's visit time. In this paper, we develop an intelligence website knowledge extraction system by analysis the web logs. Using it, web manager can get the user's latent evaluation to the web at any moment, adjust the improper web structure, and grasp the visit statue of the whole web site resource.Intelligence website knowledge extraction system includes the data preprocess, data warehouse subsystem based on OLAP technology, knowledge extraction subsystem based on web log mining. By analyzing the Web logs, the system can discover general web access patterns; find the target pages association rule; implement the adjustment and reorganization of website organization; get the major sub web site structure for the mobile phone visitors; discover the personalized search engine model; present an effective method for privacy preserving association rule mining model. Data warehouse subsystem based on OLAP technology set up a data warehouse by using the huge web log, on which we can use OLAP technology, and master the visit statue of the whole web site resource.As shown in the experimental results, the algorithms presented in the intelligence website knowledge extraction system can achieve significant improvements in terms of privacy, accuracy, efficiency, and applicability.