18243883. SEMANTIC-AWARE NEXT BEST ACTION RECOMMENDATION (Microsoft Technology Licensing, LLC)

SEMANTIC-AWARE NEXT BEST ACTION RECOMMENDATION

Organization Name

Microsoft Technology Licensing, LLC

Inventor(s)

Guillaume Didier Jean-Marc Dufour of Petaluma CA (US)

Yang Chen of Sunnyvale CA (US)

Lukasz Janusz Karolewski of San Jose CA (US)

SEMANTIC-AWARE NEXT BEST ACTION RECOMMENDATION

This abstract first appeared for US patent application 18243883 titled 'SEMANTIC-AWARE NEXT BEST ACTION RECOMMENDATION

Original Abstract Submitted

In an example embodiment, an embedding model is used to generate an embedding of a natural language searching goal specified by a user, the embedding representing user intent of the user. Playbooks in a database of playbooks are also run through the embedding model to generate an embedding for each playbook indicative of a meaning of each playbook. A semantic relationship score can then be computed for each combination of the natural language search goal and a playbook, using the embeddings. These semantic relationship scores can then be passed into a ranking machine learning model, along with measured success rates for the playbooks, to generate a ranking of the playbooks. Based on this ranking, a set of filters and action corresponding to at least one of the playbooks may then be recommended to the user.