Web Log Mining Research And Data Preprocessing Algorithm

The swift and violent development of Internet,especially the whole worlds of Web popularizes and Web incomparably abundant amount of information.Through Web mining, we can draw necessary knowledge from Web page: to analyze the contents to total user receive and visit behavior and frequentness,we can get the general knowledge of behavior and mode of users, and use that to improve our web serve. And more importance, through the understanding and analyzing of user'scharacteristic, it can help and develop the electronic commercial activities.As a confluence of data mining and WWW technologies, it is possible to perform data mining on web log records collected from the Internet web page access history. Web Usage Mining is the application of Data mining techniques to discover usage patterns from Web data in order to understand and serve the needs of Web-based applications. It is necessary to optimaize the structure of Web sit and to supply the individuation service.Now Web Usage Mining is hotspot of Data Mining, and it is also one of the major topics on Web log mining. More meaningful sequence patterns be found is the final purpose of the thesis.In this thesis,the process of data mining,web data mining and web log mining was reported.Focusing on the web log mining,the method and technology of web log mining were discussed in this thesis. Because of multi-frame can reduce the interestingness of Web log mining results , the thesis put forward a refined Web log preprocessing technology called frame-filtering. Our experiments show that by filerating subframe page requests that are not directly generated by user clicks, the frame-filterning algorithm can improve the interestingness of web log mining results.