Smart two level K-means algorithm to generate dynamic user pattern cluster

Abstract

Data cleaning perform in the Data Preprocessing and Mining. The clean data work of web server logs irrelevant items and useless data can not completely removed and Overlapped data causes difficulty during retrieving data from datasource. Previous paper had given 30% performance of datasource. So We have Implemented Smart Two-level clustering method to get pattern data for mining. This paper presents WebLogCleaner can filter out much irrelevant, inconsistent data based on the common of their URLs and it is going to improving 8% of the data quality, performance, Accuracy and efficiency of any Datasource.