Paper Title
Comparative Study Between Density Based Clustering - DBSCAN and Optics

Data mining is process of retrieving data and patterns from large database. Clustering is a phase of data mining that cumulates the data and finds a proven structure from the database. A good clustering approach plays a major role in detecting clusters of arbitrary shapes. In this paper I have discuss about the Density Based Clustering Spatial Clustering of Applications with Noise (DBSACN) which finds out clusters of different shapes and size from a large database and improves scalability and efficiency in a multiphase clustering. With this Ordering Points to Identify the Clustering Structure (OPTICS) have been compared to identify similar objects based on their density, here one produces clusters and the other outputs augmented ordering representing density-based structure of a database. The parameters and their optimisations are also discussed. Keywords— Clustering, density-based clustering, DBSCAN, OPTICS.