Adobe, Inc.

Jiabin Geng

Ryan A Rossi

William Brandon George

Sungchul Kim

Iftikhar Ahamath Burhanuddin

Ritwik Sinha

Xiang Chen

Uttaran Bhattacharya

Said Kobeissi

Guillaume L Escarguel

Prithvi Bhutani

Abhisek Trivedi

Andrei Zugravu

Brandon Galen Mooso

Razvan-Alexandru Balan

Harshita Chopra

MD Mehrab Tanjim

Techniques for data question answering with auxiliary recommendations are described to enable efficient querying of data sets for answers to data questions based on a natural language input. In an example, a processing device is operable to receive a natural language input including a query, determine an additional query based on a context of the query, and query a machine-learning model using the query and the additional query. The processing device is further operable to receive, from the machine-learning model, a result including a quantitative answer to the query, an additional answer based on the additional query, and an explanation by the machine-learning model of how the machine-learning model generated the quantitative answer or the additional answer in response to the querying. The processing device is operable to present the result for display in a user interface.

Data question answering with auxiliary recommendations

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Lehi, UT, United States of America

Jiabin Geng