Microsoft Technology Licensing, LLC

Corby Louis Rosset

Paul Nathan Bennett

Chenyan Xiong

Saurabh Kumar Tiwary

Xia Song

Daniel Fernando Campos

Nicholas Eric Craswell

Nicholas Craswell

A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Using a multi-task-trained neural network to guide interaction with a query-processing system via useful suggestions

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Seattle, WA, United States of America

Corby Louis Rosset