Identifying Peculiar Data in Multi Data Bases Using Clustering Technique
A new class of rules which are discovered by searching relevance among peculiar data are peculiarity rules. These rules are mined and explained in a relational mining framework. A main task in mining is peculiarity identification. Peculiarity rules are a new class of rules which can be discovered by searching relevance among a relatively small number of peculiar data. Peculiarity oriented mining in multiple data sources is different from, and complementary to, existing approaches for discovering new, surprising, and interesting patterns hidden in data. This paper describes both the attribute level and record level peculiarity to generate rules. Several experiments are carried out to illustrate peculiarity-oriented mining. In this paper, a framework for peculiarity oriented mining is presented.