Clustering Perspective in Attribute Based data Set in the Collaborative Learning Behavior

Abstract

Technology has its own way to understand the aspect of human social life, in this prospect we consider collective context in the sense of an individual scalability of the Data set in the perspective of considering the network is a network that relies on computing power of its clients rather than in the network itself on attribute. a set of information-theoretic techniques based on clustering that discover duplicate, or almost duplicate, tuples and attribute values in a relation instance. From the information collected about the values, we then presented an approach that groups attribute so that duplication in each group is as high as possible. The groups of attributes with large duplication provide important clues for the re-design of the schema of a relation. We consider the context using these clues, since we consider the node mechanism flow putting forward to the level of highest cluster in the social networking domain