Construing similarities between datasets with explainable cognitive methods

Abstract

In an approach for construing similarities between datasets, a processor accesses a pair of sets of feature weights, wherein the sets of feature weights include a query dataset and comprises first weights associated to first features and a reference dataset and comprises second weights associated to second features. Based on similarities between the first features and the second features, a processor discovers flows from the first features to the second features, wherein the flows maximize an overall similarity between the pair of sets of feature weights. Based on the similarities and the flows, a processor computes pair contributions to the overall similarity in order to obtain contributive elements, wherein the pair contributions are contributions of pairs joining the first features to the second features. A processor ranks the contributive elements to obtain respective ranks. A processor returns a result comprising the contributive elements and indications to the respective ranks.