Entity Resolution-Based Jaccard Similarity Coefficient for Heterogeneous Distributed Databases

Entity Resolution (ER) is a task for identifying same real world entity. It refers to data object matching or deduplication. It has been a leading research in the field of structure database. Due to its significance, entity resolution continues to be a most important challenge for heterogeneous distributed databases. Several methods have been proposed for the Entity resolution, but they have yielded unsatisfactory results. In this paper, we propose an efficient integrated solution to the entity resolution problem based on Jaccard similarity coefficient. Here we use Markov logic and Jaccard similarity coefficient for providing an efficient solution towards ER problem in heterogeneous distributed databases. The approach that we have implemented gives an overall success rate of about 98 %, thus proving better than the previously implemented algorithms.