International Business Machines Corporation
Multiclassification approach for enhancing natural language classifiers

Abstract:

In an approach to creating models utilizing optimally clustered training sets, one or more computer processors determine an optimal cluster size. The one or more computer processors generate one or more clusters from one or more classes and respectively associated training statements that are contained in a training set, based on the determined optimal cluster size, wherein the one or more generated clusters, respectively, contain fewer classes than the training set. The one or more computer processors identify one or more isolated high confidence classes and associated training statements from one or more cluster classifications generated by a static model trained with the one or more generated clusters. The one or more computer processors create one or more dynamic models trained with the one or more identified isolated high confidence classes. The one or more computer processors perform one or more classifications utilizing the one or more created dynamic models.