Real-time on the fly generation of feature-based label embeddings via machine learning
The present disclosure is directed to systems and methods that include a machine-learned label embedding model that generates feature-based label embeddings for labels in real-time, in furtherance, for example, of selection of labels relative to a particular entity. In particular, one example comput...
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Main Authors | , , |
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Format | Patent |
Language | English |
Published |
13.09.2022
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Subjects | |
Online Access | Get full text |
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Summary: | The present disclosure is directed to systems and methods that include a machine-learned label embedding model that generates feature-based label embeddings for labels in real-time, in furtherance, for example, of selection of labels relative to a particular entity. In particular, one example computing system includes both a machine-learned entity embedding model configured to receive and process entity feature data descriptive of an entity to generate an entity embedding for the entity and a machine-learned label embedding model configured to receive and process first label feature data associated with a first label to generate a first label embedding for the first label. |
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Bibliography: | Application Number: US201916551829 |