Bank of America Corporation

Bank of America Corportion

James McCormack

Manu Jacob Kurian

Sasidhar Purushothaman

Suki Ramasamy

William P Jacobson

Sean Michael Gutman

Jisoo Lee

Monika Kapur

Rick A Beye

Shakti Suman

Konstantin Shushkovsky

A Ugur Tigli

A natural language processing system that includes an artificial intelligence (AI) engine and a tagging engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tagging engine is configured to receive an audio file and to identify observed concepts within the audio file. The tagging engine is further configured to compare the observed concepts to the first set of concepts, to determine one or more observed concepts matches concepts linked with AI-defined tags, and to modify metadata for the audio file to include AI-defined tags.

Dynamic natural language processing tagging

A natural language processing system that includes an artificial intelligence (AI) engine and a tag management engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tag management engine is configured to receive an audio file, identify tags linked with the audio file, to determine an access frequency for the audio file within a predetermined time period, and to adjust the activity level of the tags based on the access frequency. The tag management engine is further configured to remove tags from the set of tags with an activity level that is less than a purge threshold.

Resource management using natural language processing tags

A natural language processing system that includes an artificial intelligence (AI) engine, a tagging engine, and a resource allocation engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tagging engine is configured to receive an audio file and to modify metadata for the audio file to include AI-defined tags. The resource allocation engine is configured to identify a storage location from among the plurality of storage devices based on tags associated with the audio file and send the audio file to the identified storage location.

Dynamic memory allocation using natural language processing tags

In one or more embodiments, one or more systems, processes, and/or methods may receive first task sets that include respective first tasks and one or more of respective first priorities, respective first minimum computing resource allocations, and respective first maximum processing times; receive first satisfaction information associated with processing the first task sets; receive first execution metric information associated with processing the first task sets; determine a first pattern based at least on the first satisfaction information and based at least on the first execution metric information; receive second task sets that include respective second tasks and one or more of respective second priorities, respective second minimum computing resource allocations, and respective second maximum processing times; determine, based at least on the first pattern, computing resources allocations for the second task sets; and determine, based at least on the first pattern, a processing order for the second task sets.

System and method of training machine learning algorithm to satisfactorily allocate resources for task execution

In one or more embodiments, one or more systems, processes, and/or methods may receive a first data stream and determine a pattern from the first data stream. At least one rule set based at least on the pattern may be determined. A second data stream, different from the first data stream may be received and entities may be determined, where each of the entities may be associated with respective data of the second data stream that satisfies the at least one rule set. At least one data object of the second data stream may be tagged, in response to determining the entities. In one or more embodiments, tagging the at least one data object may associate the at least one data object with at least one of the entities.

Growing community of inventors

Charlotte, NC, United States of America

James McCormack