Research On An Approach Of OLAP And Client Data Mining In Business Intelligence

In the future, the development pattern of commerce economy is a business pattern which takes customer as center and is service oriented. This pattern's core is perfect service ensures system and high-effect management control strategy. Web-log analysis and mining is an application of business intelligence whose purpose is to improve service quality through understanding web browsers' interest. This dissertation applies XML in OLAP, aiming at analysis and mining web-log. There are several aspects this dissertation does as fallows:1. This dissertation has analyzed the advantages of data description with XML and introduced some applications of XML in OLAP system.2. A process of OLAP and data mining based on XML is proposed. This process takes isomerous data source integration into account and use data cube with XML. In this process, OLAP system and data mining system associate, and the result of analysis and mining is released with internet.3. This dissertation has analyzed concretely the technologies involved in the process of OLAP and data mining based on XML, such as isomerous data source integration based on XML; Has introduced a multi-dimension expression based on XML, which is used to construct data cube and multi-selection; Has introduced the method of describing Web-log with XML.4. A method which makes users clustering with the rate of interest of users toward web page classes is proposed. This method ignores the hits amounts, set web page weight with its content and depth. It can be considered as a method with users' macro interest. At last, this dissertation analyzed the difference between this method and traditional ones.The research done by this dissertation, have provided certain reference value for the research of OLAP based on XML and its application in web log analysis and mining, and the research of web-log clustering.