Patents by Inventor Joel M. HRON, II

Joel M. HRON, II has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11954098
    Abstract: In various embodiments, the disclosed systems and methods may receive documents, analyze the documents, categorize portions of the analyzed documents, and present the images of the documents and at least a portion of the categories. The analysis may include identification of categories and the presentation may include indicia of the portion of the image of the document related to the category. The systems and methods disclosed may allow querying and/or reporting of a plurality of documents to facilitate processing.
    Type: Grant
    Filed: June 27, 2019
    Date of Patent: April 9, 2024
    Assignee: Thomson Reuters Enterprise Centre GmbH
    Inventors: Joel M. Hron, II, Nicholas E. Vandivere, Michael B. Kuykendall
  • Patent number: 11909858
    Abstract: A semantic parser can process natural language of a traditional contract to generate variables and rules which can be implemented in a smart contract. The smart contract can be provided to a distributed ledger, such as a blockchain network, to execute the smart contract. Execution of the smart contract can be documented in the distributed ledger and in association with the smart contract.
    Type: Grant
    Filed: June 21, 2019
    Date of Patent: February 20, 2024
    Assignee: Thomson Reuters Enterprise Centre GmbH
    Inventors: Joel M. Hron, II, Nicholas E. Vandivere, Michael B. Kuykendall
  • Publication number: 20230326225
    Abstract: Aspects of the present disclosure involve systems and methods for an automated machine learning partitioning of a digital image file into multiple documents. The machine learning system may obtain or receive a digital image file that includes multiple documents merged into the single image file. To determine the different documents included in the image file, the machine learning model may analyze the content of the pages of the image file to determine particular content that may indicate the start and/or end of documents within the image file and partition the image file into multiple documents based on the determined start and/or end of the documents. In one instance, the machine learning partitioning system may generate an analysis window that comprises two pages of the corpus of pages and compare features or content of the two pages or determine if either of the two pages includes one or more features.
    Type: Application
    Filed: April 4, 2023
    Publication date: October 12, 2023
    Inventor: Joel M. HRON, II
  • Publication number: 20230326222
    Abstract: Aspects of the present disclosure involve an automated, machine-learning technique for generating a representation of an ontology of a corpus of documents. This unsupervised generation of the ontology of the content of the documents may describe, based on the semantics of the language in the corpus and on the structure and format of the documents in that corpus, potentially key differentiable topics and sub-topics within the documents and the potential relationship between the topics and sub-topics. The unsupervised, or automated, generation of the ontology may provide a foundation of potential topics and sub-topics of a corpus of documents from which a complete ontology for the corpus of documents may be created. This ontology may be both pertinent in defining a structure through which an end user may interpret the data identified from a document or set of documents and/or to inform a machine-learning model to extract document information and classification.
    Type: Application
    Filed: April 4, 2023
    Publication date: October 12, 2023
    Inventor: Joel M. HRON, II
  • Publication number: 20230134989
    Abstract: Aspects of the present disclosure involve systems and methods for automated analysis of documents to obtain attributes associated with those documents, and using the attributes to organize, relate, and/or aggregate documents. Attributes can be applied to the document or inferred from the document based on a machine learning model. One or more of either of these types of attributes can be used to relate documents together, join them together, or aggregate them with their associated metadata into a composite result. The aggregation of attributes may include rules for how attributes are to be aggregated. In one implementation, a document management system may receive a collection of documents and scan the documents to create a corresponding image for use in aggregating the documents. An artificial intelligence or machine learning technique may then be applied to the collection of documents to extract or otherwise determine attributes or data from the documents.
    Type: Application
    Filed: November 3, 2022
    Publication date: May 4, 2023
    Inventors: Joel M. HRON, II, Nicholas E. VANDIVERE, Daniel DROKE
  • Publication number: 20220164714
    Abstract: A method performed by a machine learning system that involves obtaining a first ontology that includes one or more labels. Each label is associated with a sample that includes text. The ML system is configured to use a particular label to retrieve one or more samples associated with the particular label. The method further involves receiving an identification of a label of a first ontology associated with a first machine learning model to share with a second ontology associated with a second machine learning model and sharing the label and the information with the second ontology. The method further involves training the second machine learning model using the shared information associated with the label.
    Type: Application
    Filed: November 22, 2021
    Publication date: May 26, 2022
    Inventor: Joel M. HRON, II