MACHINE LEARNING TECHNIQUES FOR QUESTION RESOLUTION

Abstract: various embodiments of the present disclosure provide machine-learning question resolution techniques for improving question response outputs. the techniques may include receiving a plurality of evidence passages from a document set corresponding to an input question. the techniques may include generating, using a retrieval ensemble model, a plurality of evidence predictions for an evidence passage of the plurality of evidence passages based on the input question. the techniques may include generating, using the retrieval ensemble model, a weighted aggregate prediction for the evidence passage based on the plurality of evidence predictions. the techniques may include selecting, a set of input passages from the plurality of evidence passages based on the weighted aggregate prediction. the techniques may include generating, using a machine learning aggregation model, a question response based on the set of input passages and the input question. the techniques may include providing the question response.

Inventor(s): Ardavan Saeedi, Jagadish Venkataraman, Joel David Stremmel, Hamid Reza Hassanzadeh

CPC Classification: G06F16/383 (Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually)

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