Implementation of Many-to-Many Data Linkage using OCCT for Matching and Non- Matching Pairs
Data linkage is a process performed among entities of the same type or different type. It is necessary to develop the data linkage techniques for different types as well. In this paper, we propose a many-to-many data linkage and it is used to perform link between matching entities of different types. The proposed method is based on One-Class Clustering Tree (OCCT) for implementing many-to-many data linkage. The OCCT is built in such a way that it is easy to understand and can be transformed into association rules. The inner node consists of features from the first data set. The leaves of the tree represent features from the second data set that is matching with the first data set entities. The proposed method uses maximum-likelihood estimation for pre-pruning process which is used to create One-Class Clustering Tree effectively. Threshold value is used for decision making either the record pair is match or non-match.