Machine learning techniques for natural language processing using predictive entity scoring

There is a need for more accurate and more efficient natural language solutions with greater semantic intelligence. This need can be addressed, for example, by natural language processing techniques that utilize predictive entity scoring. In one example, a method includes determining an overall prev...

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Main Authors Funk, Nathan H, Jensen, Amy L, Bali, Raghav, Chikka, Veera Raghavendra, Rao, M. P. S. Jagannadha, Appe, Anudeep Srivatsav, Maji, Subhadip, Tryon, Eric D, Ponnala, Sudheer
Format Patent
LanguageEnglish
Published 26.12.2023
Subjects
ACOUSTICS
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
MUSICAL INSTRUMENTS
PHYSICS
SPEECH ANALYSIS OR SYNTHESIS
SPEECH OR AUDIO CODING OR DECODING
SPEECH OR VOICE PROCESSING
SPEECH RECOGNITION
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Summary:There is a need for more accurate and more efficient natural language solutions with greater semantic intelligence. This need can be addressed, for example, by natural language processing techniques that utilize predictive entity scoring. In one example, a method includes determining an overall prevalence score for the input entity data object with respect to a scored document corpus and a target section; determining a qualified prevalence score for the input entity data object with respect to a high-scoring subset of the scored document corpus; processing the input entity data object using an entity scoring machine learning model to generate the predicted entity score, wherein the entity scoring machine learning model may characterized by a plurality of multiplicative hyper-parameters and one or more additive hyper-parameters; and performing one or more prediction-based actions based at least in part on the predicted entity score.
Bibliography:Application Number: US202318161969