EFFICIENTLY CORRELATING NOMINALLY INCOMPATIBLE TYPES

Patent №

US 9,201,874

Granted

2015-12-01

Filed 2008

Owner

MICROSOFT CORPORATION

AI components

2

kr · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

12036471

A nominal type framework can be configured to efficiently correlate different nominal types together based on a minimum set of common type shapes or structures. In one implementation, a developer identifies a number of different nominal types of interest (source types), and identifies the minimum set of common type shapes to be accessed by an application program. The minimum set of common type shapes can then be used to create an intermediate type (target type) to which each of the other different source types can be mapped. For example, one or more proxies can be created that map shapes of the one or more source types to corresponding shapes of the created target type. The application program created by the developer, in turn, can access, operate on, or otherwise use the mapped data of each different source type through a single target type.

AI classification

Knowledge representation0.99
AI hardware0.97
Natural language0.01
Vision0.00
Planning0.00
Speech0.00
Evolutionary computation0.00
Machine learning0.00

Ownership

MICROSOFT CORPORATION

assignment · 205560150

Assignors

SZYPERSKI, CLEMENS A., BRADLEY, QUETZALCOATL, WILLIAMS, JOSHUA R., ANDERSON, CHRISTOPHER L., BOX, DONALD F., PINKSTON, JEFFREY S., GUDGIN, MARTIN J.

On an employer assignment, the assignors are typically the inventors.

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