DEVELOPMENT OF PATTERN KNOWLEDGE DISCOVERY FRAMEWORK USING CLUSTERING DATA MINING ALGORITHM

Abstract

The prime objective of this research work is to identify a pattern of clustering and extend to improve the use of Web Data Mining. This extension helps to sensitize Knowledge Discovery and Business Improvement Intelligence. The motivation is to analyze user access patterns and improve the access privileges of the users. These improved access privileges helps to channelize the analysis for optimized selection of objects. This work obtained secondary dataset of CPU processors from the web data repository UCI. The dataset was subjected to the application of the techniques of statistics, machines learning, and clustering data mining. The selection of appropriate Web Mining Technique is a challenge for Knowledge Discovery. The selection primarily depends upon the nature of a dataset. To obtain optimized solution to the challenge, proposed work uses the Clustering Data Mining techniques. The results obtained there at are analyzed to optimum outcome of data. To achieve optimum result this work has proposed a framework Pattern Knowledge Discovery for macro level and micro level pattern evaluation and test the proposed framework with its implementation for the purpose of justification of the work.