Adobe, Inc.

Arjun Athreya

Eunyee Koh

Michele Saad

Irgelkha Mejia

Lauren Dest

Dustin Ground

Anna Hammond

Catherine Chiodo

Andrew Thomson

Methods, systems, and non-transitory computer readable media are disclosed for utilizing machine learning models to extract digital signals from low-results web queries and generate item demand deficiency predictions for digital item lists corresponding to websites. In one or more embodiments, the deficiency identification system identifies a low-results query submitted by client devices navigating a website. The deficiency identification system generates features for the low-results query and the digital item list to generate a deficiency prediction relative to demand indicated by the low-results query. In some embodiments, the deficiency identification system utilizes a deficiency prediction model to process the extracted signals and generate a deficiency confidence score corresponding to the low-results query. Based on the deficiency confidence score, the deficiency identification systemd can generate and provide demand notifications via one or more graphical user interfaces.

Utilizing machine learning models to process low-results web queries and generate web item deficiency predictions and corresponding user interfaces

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Austin, TX, United States of America

Arjun Athreya