Capital one services, llc (20240346077). DETERMINING DATA CATEGORIZATIONS BASED ON AN ONTOLOGY AND A MACHINE-LEARNING MODEL simplified abstract

DETERMINING DATA CATEGORIZATIONS BASED ON AN ONTOLOGY AND A MACHINE-LEARNING MODEL

Organization Name

capital one services, llc

Inventor(s)

Kai-Wen Chen of Arlington VA (US)

Brian Donohue of Warrenton VA (US)

Xuemei Pan of Great Falls VA (US)

Nirmal Kumar Raajan of Irving TX (US)

Bethany Sehon of Oakton VA (US)

Naresh Singh of Frisco TX (US)

Xiaofei Wang of Bellevue WA (US)

Albert T. Zellers of McLean VA (US)

Weidan Zhou of Frisco TX (US)

DETERMINING DATA CATEGORIZATIONS BASED ON AN ONTOLOGY AND A MACHINE-LEARNING MODEL - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240346077 titled 'DETERMINING DATA CATEGORIZATIONS BASED ON AN ONTOLOGY AND A MACHINE-LEARNING MODEL

The abstract of this patent application describes methods, systems, and apparatuses for determining categories associated with a dataset based on tags and descriptions.

• The determination of categories may involve searching an ontology or using a machine-learning model.
• The identified categories can be used to modify or validate the dataset.

1. 1. 1. Potential Applications:

This technology could be applied in data management systems, content tagging, and information retrieval systems.

1. 1. 1. Problems Solved:

This technology addresses the challenge of categorizing and organizing large datasets efficiently.

1. 1. 1. Benefits:

The benefits of this technology include improved data organization, enhanced search capabilities, and streamlined data validation processes.

1. 1. 1. Commercial Applications:

Title: Data Categorization Technology for Enhanced Information Management This technology could be commercially used in data analytics companies, digital asset management systems, and online content platforms.

1. 1. 1. Prior Art:

Researchers interested in this technology may want to explore prior art related to data categorization, ontology-based data processing, and machine learning models for data classification.

1. 1. 1. Frequently Updated Research:

Researchers in the field of data management and information retrieval are continuously exploring new methods and technologies for improving data categorization processes.

1. 1. 1. 1. Questions about Data Categorization Technology:

1. What are the key advantages of using machine learning models for data categorization?

  - Machine learning models can automatically learn patterns and relationships in data, making them effective for categorization tasks.
  

2. How does ontology-based data processing enhance the accuracy of category determination?

  - Ontologies provide a structured framework for organizing data and relationships, improving the precision of category assignments.

Original Abstract Submitted

aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. the determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. the determination may be performed by using a machine-learning model based on the one or more tags and/or the description. once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.