Journals Proceedings

Abstract

Frequent pattern mining algorithm is an interesting problem and most essential field in data mining, a Navigation pattern defines the user’s behavior towards a particular area, in this paper we propose an algorithm for mining user navigation Patterns using frequent item sets, by using transaction Reduction method. By using Association rule mining we extract the interesting Correlation and relation between the large volumes of Transactions in the databases. In this paper we merge the navigation pattern mining algorithm with the Content based image retrieval application. Thus by merging it we obtain an effective knowledge discovery process by which it overcomes the draw backs of the existing system This work thus used to extract the navigation patterns discovered from the data bases used in the Content Based image retrieval. And also this work is used as the offline Knowledge discovery process in CBIR.