IJCTT-International Journal of Computer Trends and Technology
Data mining discovers know-how required for decision making. In real world high-dimensional data is frequently used. Therefore it is essential for data mining techniques to work on high-dimensional data. Especially clustering algorithm has to work with high-dimensional data. In this paper the authors explore the similarity search mechanisms with respect to high-dimensional data. The existing techniques for indexing have certain drawbacks as they do not consider dependencies. For this reason their performance is suboptimal. In the process of clustering finding correlations of different dimensions is required.