This paper describes a case study of knowledge discovery from web access logs of an e-commerce site. It is important for e-commerce sites to analyze the behavior of visitors from web access log to increase sales and recurring users. In order to support the tasks, we use a visualization method both trend and relationships called FACT-Graphs with Sequential Probability Ratio Test for detecting trend change points. In an experiment for the data of a Web shop in Japan, we could extract 14 trend change points, visualize information both trend and relationships, and extract useful knowledge of the improvement of navigation for visitors.
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