The Design And Implementation Based On Web Log Mining System

As the fast developing and spreading of Internet, Web usage information grows quickly. People begin to pay close attention to mining valuable information from large amount of data. The World Wide Web (WWW) continues to grow at an astounding rate in both the sheer volume of traffic and the size and complexity of Web sites. The complexity of tasks suck as Web site design, Web server design, and of simply navigating through a Web site have increased along with this growth. An important input to these design tasks is the analysis of how a Web site is being used. Log analysis includes straightforward statistics, such as page access frequency, as well as more sophisticated forms of analysis, such as finding the common traversal paths through a Web site. Web Log Mining is the application of data mining techniques to server logs of large Web data repositories in order to produce results that can be used in the design tasks mentioned above.In our research, we explain the concept, research works, key technologies of Web log mining and related research at home and abroad, and then use data mining technology to analyze the Web usage information of one district government so as to find out the usage pattern and preference of enterprises and individuals as the better decision-making aid for website executives. The thesis achieves the following tasks: first, studying the preprocessing of raw Web log, analyzing the difficulties and describing the process, such as data cleaning, user identification, session identification, path supplement; second, on the base of anatomizing classical Apriori Algorithm, improving the performance by reducing the number of item sets and developing a new algorithm, called M-Apriori ; third, studying...