Abstract:
The rising popularity of electronic commerce makes data mining an indispensable technology for several applications, especially online business competitiveness. The World Wide Web provides abundant raw data in the form of web access logs. However, without data mining techniques, it is difficult to make any sense out of such massive data. In this paper focus on the mining of web access log, commonly known as Web usage mining. Frequent pattern mining is a heavily researched area in the field of data mining with wide range of applications. One of them is to use frequent pattern discovery methods in Web log data. Discovering hidden information from Web log data is called Web usage mining. The aim of discovering frequent patterns in Web log data is to obtain information about the navigational behavior of the users. This can be used for advertising purposes, for creating dynamic user profiles etc.In this paper, GSP algorithm is used for sequential pattern mining in web log data.
