Adobe, Inc.

Ming Liu

Jayant Kumar

Jing Zheng

Vipul Dalal

Ashok Gupta

Ravindra Sadaphule

Andrei Stefan

Manasi Deshmukh

Chirag Arora

Karthik Suresh

This disclosure describes methods, non-transitory computer readable storage media, and systems that generate a digital knowledge graph based on a plurality of tutorial content items to generate recommendations of digital resource items. Specifically, the disclosed system extracts a plurality of tasks, subject categories related to the tasks, and context signals related to an environment for the tasks from a plurality of tutorial content items for one or more digital content editing applications. The disclosed system generates a digital knowledge graph including nodes corresponding to the tasks and subject categories connected via edges based on relationships extracted from the tutorial content items. In some embodiments, the disclosed system also includes nodes corresponding to digital resource items in the digital knowledge graph or in a subgraph. The disclosed system utilizes the digital knowledge graph with context data to provide a recommendation of digital resource items for display at a client device.

Generating and utilizing a digital knowledge graph to provide contextual recommendations in digital content editing applications

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Sunnyvale, CA, United States of America

Ming Liu