International Business Machines Corporation

Richard John Oswald

Jing-Yun Shyr

Jean-Francois Puget

Yea-Jane Chu

Vikremjeet Singh Bhagi

Using a natural language processing (NLP) engine executing in conjunction with a machine that is engaged in first natural language interaction, an analytics intent comprising an analysis type to be performed on a dataset is extracted from the first natural language interaction. Within the dataset, a subset of the dataset comprising data having above a threshold relevance measure with respect to the analytics intent is identified. From the subset, a knowledge graph modeling a set of relationships between data in the subset is constructed. Using the analytics intent and the knowledge graph, a conversational template is customized, augmenting the conversational template with a set of entities corresponding to the analytics intent. To obtain a result, the subset is analyzed using the knowledge graph. A second natural language interaction is presented via the machine, the presenting comprising transforming by the NLP engine the result to fit the customized conversational template.

Natural language interaction based data analytics

A computer-implemented method for prescriptive time-series forecasting, which combines both what-if analysis and goal-seeking analysis. The method comprises building a model for a target metric with a set of predictors, based on historical time-series data, and computing, using the model, a set of forecast values. Using the set of forecast values with respect to a forecasting period, both a set of goals for the target metric and a set of constraints for the predictors are analyzed. A set of updated forecasts based on the analyses with respect to the forecasting period is determined to meet the goals within the set of constraints. The updated set of forecasts is presented with respect to the forecasting period, e.g., using a table, a visualization, and/or an interactive user interface.

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Chicago, IL, United States of America

Richard John Oswald