Semantic-aware next best action recommendation
AssigneeMicrosoft Technology Licensing, LLC
InventorsGuillaume Didier Jean-Marc Dufour, Yang Chen, Lukasz Janusz Karolewski
Life of this patent
Estimating the term…
Loading patent…
AssigneeMicrosoft Technology Licensing, LLC
InventorsGuillaume Didier Jean-Marc Dufour, Yang Chen, Lukasz Janusz Karolewski
Estimating the term…
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.
A method, comprising:
An apparatus, comprising:
A non-transitory machine readable medium comprising instructions that when executed by circuitry causes the circuitry to:
Dependencies are inferred from the claim text.