Microsoft technology licensing, llc (20240303434). CLASSIFICATION AND AUGMENTATION OF UNSTRUCTURED DATA FOR AUTOFILL simplified abstract

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CLASSIFICATION AND AUGMENTATION OF UNSTRUCTURED DATA FOR AUTOFILL

Organization Name

microsoft technology licensing, llc

Inventor(s)

Shrey Shah of Redmond WA (US)

Timothy Franklin of Seattle WA (US)

Irfan Ahmed of Hyderabad (IN)

Bryan Miller of London (GB)

Anand Balachandran of Bellevue WA (US)

CLASSIFICATION AND AUGMENTATION OF UNSTRUCTURED DATA FOR AUTOFILL - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240303434 titled 'CLASSIFICATION AND AUGMENTATION OF UNSTRUCTURED DATA FOR AUTOFILL

The abstract of this patent application describes systems, methods, and devices for classifying text strings, augmenting text strings, and identifying classified text strings for intelligent autofill.

  • A fact store is populated with facts from various data sources associated with a user account, including unstructured, semi-structured, and structured data.
  • The intent type of a text string displayed on a local computing device is determined, which may be form data or freeform data.
  • The context of the local computing device is also determined.
  • Based on the intent type and context, a text string corresponding to a fact in the fact store is identified for surfacing on the local computing device.
      1. Potential Applications:

This technology can be applied in various fields such as data management, information retrieval, and personalized user experiences.

      1. Problems Solved:

This technology addresses the challenges of efficiently classifying and augmenting text strings for intelligent autofill, improving user productivity and experience.

      1. Benefits:

The benefits of this technology include enhanced data organization, streamlined information retrieval, and personalized content suggestions for users.

      1. Commercial Applications:

This technology can be utilized in software applications, search engines, e-commerce platforms, and any system that requires efficient text classification and augmentation for user convenience.

      1. Questions about the Technology:

1. How does this technology improve user productivity? 2. What are the key factors considered in determining the intent type of a text string?

      1. Prior Art:

Researchers can explore prior art related to text classification, data augmentation, and intelligent autofill systems to understand the evolution of similar technologies.

      1. Frequently Updated Research:

Stay informed about the latest advancements in text classification, data augmentation, and intelligent autofill systems to leverage cutting-edge developments in this field.


Original Abstract Submitted

in non-limiting examples of the present disclosure, systems, methods and devices for classifying text strings, augmenting text strings, and identifying classified text strings for intelligent autofill are provided. a fact store may be populated with facts from a plurality of data sources associated with a user account. the fact store may comprise unstructured data, semi-structured data, and structured data. an intent type associated with a text string displayed by a local computing device may be determined. the text string may comprise form data or freeform data. a context associated with the local computing device may also be determined. based on the intent type and the context, a text string corresponding to a fact in the fact store may be identified for surfacing on the local computing device.

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