Company Filing History:
3 out of 4 Years Active: 2020-2024
Title: Innovations of Joseph M. Wood
Introduction
Joseph M. Wood is an accomplished inventor based in Broadlands, VA (US). He has made significant contributions to the field of predictive analysis through his innovative patents. With a total of four patents to his name, Wood has established himself as a key figure in the application of machine learning technologies.
Latest Patents
One of Joseph M. Wood's latest patents focuses on predictive analysis systems and methods using machine learning. This invention involves systems and methods that utilize a predictive analysis model to analyze contracts or other documents. The system is designed to parse a document and/or a repository of information associated with it. It identifies terms in the document and corresponding terms in the repository. Furthermore, the system determines a difference parameter between a first term extracted from the document and a second term from the repository. It assesses whether the difference is likely to be acceptable to the user, using the predictive analysis model. The system also reports a validation parameter indicating the level of acceptability associated with the difference. User feedback on the accuracy of the predictive analysis model is utilized to train, modify, and improve the model.
Career Highlights
Joseph M. Wood has been instrumental in advancing predictive analysis technologies. His work has garnered attention for its innovative approach to document analysis and user interaction. He is currently associated with Deepsee.ai Inc., where he continues to develop cutting-edge solutions in the field.
Collaborations
Some of his notable coworkers include Robert D. Bailey and Matthew Valley. Their collaboration has contributed to the success of various projects within the company.
Conclusion
Joseph M. Wood's contributions to predictive analysis and machine learning exemplify the impact of innovation in technology. His patents reflect a commitment to enhancing the accuracy and usability of predictive models.