The Integrating Between Web Usage Mining and Data Mining Techniques

Clickstream data is one of the most important sources of information in websites usage and customers' behavior in Banks e-services. A number of web usage mining scenarios are possible depending on the available information. While simple traffic analysis based on click stream data may easily be performed to improve the e-banks services. The banks need data mining techniques to substantially improve Banks e-services activities. The relationships between data mining techniques and the Web usage mining are studied. Web structure mining, has three types these types are web usage structure, mining data streams and web content. The integration between the Web usage mining and data mining techniques are presented for processes at different stages, including the pattern discovery phases, and introduces banks cases, that have analytical mining technique. A general framework for fully integrating domain Web usage mining and data mining techniques is represented for processes at different stages. Data Mining techniques can be very helpful to the banks for better performance, acquiring new customers, fraud detection in real time, providing segment based products, and analysis of the customers square purchase patterns over time.