Abstract: A method, system and computer-usable medium for augmenting the training of a conversational system. In certain embodiments, the method comprises: ingesting a training set to be used in training of the conversational system, the training set including objects for use in the training, wherein the objects include one or more object types, wherein the object types include one or more of an entity or intent; generating proposed reductions for inclusion in an augmented training set, wherein the proposed reductions include one or more of: reduction candidates generated using properties of objects included in the training set; reduction candidates obtained from search queries of one or more external resources, wherein the search queries relate to one or more objects included in the training set; filtering the proposed reductions to generate a reduced set of proposed reductions; and augmenting the training set with the reduced set of proposed reductions.

Abstract: Systems, methods, and computer program products to perform an operation comprising identifying a first available dataset having a degree of similarity to a received input dataset that exceeds a similarity threshold, determining, based on a plurality of features of the first available dataset and a plurality of features of the input dataset, a set of recommendations for transforming the input dataset, and transforming a text of the input dataset based on the set of recommendations and to optimize the input dataset for processing by a natural language processing (NLP) algorithm.

Abstract: A method, system and computer-usable medium for augmenting the training of a conversational system. In certain embodiments, the method comprises: ingesting a training set to be used in training of the conversational system, the training set including objects for use in the training, wherein the objects include one or more object types, wherein the object types include one or more of an entity or intent; generating proposed reductions for inclusion in an augmented training set, wherein the proposed reductions include one or more of: reduction candidates generated using properties of objects included in the training set; reduction candidates obtained from search queries of one or more external resources, wherein the search queries relate to one or more objects included in the training set; filtering the proposed reductions to generate a reduced set of proposed reductions; and augmenting the training set with the reduced set of proposed reductions.

Abstract: Systems, methods, and computer program products to perform an operation comprising identifying a first available dataset having a degree of similarity to a received input dataset that exceeds a similarity threshold, determining, based on a plurality of features of the first available dataset and a plurality of features of the input dataset, a set of recommendations for transforming the input dataset, and transforming a text of the input dataset based on the set of recommendations and to optimize the input dataset for processing by a natural language processing (NLP) algorithm.