Implementing One to Many Data Linkage Using One Class Clustering Tree

The task of data linkage is performed among entities of the same type. The one to one data linkage links one record from one table and another one record in another table. It is extremely necessary to develop linkage techniques that link between matching entities of different types and also to improve one to one linkage to one to many data linkage as well. The proposed method emphasizes on one-class clustering tree (OCCT). This method characterizes the entities that should be linked together. This method enables easy understanding and transformation of the clusters into association rules. The association rules indicate that the inner nodes consist of only the features describing the first set of entities, while the leaves of the tree represent features of their matching entities from the second data set. The four splitting criteria, coarse grained jaccard coefficient , fine grained jaccard coefficient, least possible intersection and two different pruning methods which can be used for inducing the OCCT.