20240046254. SYSTEM AND METHOD FOR PARSING AND TOKENIZATION OF DESIGNATED ELECTRONIC RESOURCE SEGMENTS VIA A MACHINE LEARNING ENGINE simplified abstract (Bank of America Corporation)
SYSTEM AND METHOD FOR PARSING AND TOKENIZATION OF DESIGNATED ELECTRONIC RESOURCE SEGMENTS VIA A MACHINE LEARNING ENGINE
Organization Name
Inventor(s)
Jigesh Rajendra Safary of Mumbai (IN)
SYSTEM AND METHOD FOR PARSING AND TOKENIZATION OF DESIGNATED ELECTRONIC RESOURCE SEGMENTS VIA A MACHINE LEARNING ENGINE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240046254 titled 'SYSTEM AND METHOD FOR PARSING AND TOKENIZATION OF DESIGNATED ELECTRONIC RESOURCE SEGMENTS VIA A MACHINE LEARNING ENGINE
Simplified Explanation
The present invention is a system, computer program product, and method for parsing and tokenization of designated electronic resource segments using a machine learning engine. The invention receives a request for an electronic resource and uses the machine learning engine to identify and parse one or more segments of the resource. It then predicts the number of tokens required by analyzing the resource and converts the segments into corresponding tokens. The electronic resource is transmitted to at least one user for approval, and upon receiving approval, token expiration is designated.
- The invention uses a machine learning engine to parse and tokenize electronic resource segments.
- It predicts the number of tokens required by analyzing the resource.
- The segments of the resource are converted into tokens.
- The electronic resource is sent to users for approval.
- Upon approval, token expiration is designated.
Potential applications of this technology:
- Natural language processing and text analysis
- Content management systems
- Information retrieval and search engines
Problems solved by this technology:
- Efficient parsing and tokenization of electronic resource segments
- Predictive determination of token requirements
- Streamlining approval processes for electronic resources
Benefits of this technology:
- Improved accuracy and efficiency in parsing and tokenization
- Enhanced understanding and analysis of electronic resources
- Streamlined approval processes for faster decision-making
Original Abstract Submitted
systems, computer program products, and methods are described herein for parsing and tokenization of designated electronic resource segments via a machine learning engine. the present invention is configured to electronically receive a request for an electronic resource into a machine learning engine, identify and parse one or more segments of the electronic resource using the machine learning engine, predictively determine a number of tokens required by analyzing the electronic resource using the machine learning engine, convert the one or more segments into corresponding one or more tokens, transmit the electronic resource to at least one user for approval, receive approval for the electronic resource from the at least one user, and designate token expiration.
