Using supervised learning techniques for entity relationships

Given different financial data resources, it is very challenging to relate entities across the various resources since each resource has its own way of describing the entities and relationships. We work on identifying such relationships using context and available scores, using mainly supervised machine learning techniques to build classifiers and predict new relationships or validate the existing ones based on the suitable measures of similarity.