Interactive data analysis on numeric-data
Hong Ki Chu, Man Hong Wong · 2003
Data mining has been a hot topic in computer science. Many researchers have been putting lots of effort into how to extract explicit knowledge from large databases. Among the problems in data mining, finding useful patterns in large databases has attracted lots of interest in recent years. However, like other data mining algorithms, most of the proposed clustering algorithms suffer from the same demerit: lack of user interaction and exploration. In this paper, a new algorithm called IDAN (Interactive Data Analysis on Numeric-data) is being introduced. IDAN is good in discovering clustering patterns from numeric data. This algorithm is incremental and provides more user interaction in the mining process. At the same time, it allows the user to explore the rules or clusters found when integrated with a visualizer.