SYSTEM, METHODS, AND DATA STRUCTURE FOR MACHINE-LEARNING OF CONTEXTUALIZED SYMBOLIC ASSOCIATIONS

Patent №

US 9,195,647

Granted

2015-11-24

Filed 2013

Owner

Lab

AI components

4

ml · nlp · kr · planning

Assignment

None on record

Dataset

AIPD

2023_r1 edition

Application

13802427

A system and methods and data structure for quantitatively assessing associations between terms or symbols in natural language and non-natural language contents. Some of the terms or symbols represent objects or concepts or semantic attributes; some other terms or symbols represent properties associated with the objects or concepts or semantic attributes. The methods include obtaining a first group of text contents or non-natural language data content, specifying a target term or symbol or semantic attribute, and identifying contextual attributes of the target term or symbol. The contextual attributes include grammatical and semantic attributes as well as positional and distance attributes. Association strength values are calculated for related terms or symbols based on the contextual attributes of the target term or symbol or semantic attribute.

Machine learningNatural languageKnowledge representationPlanningG06F 40/30G06F 16/313G06F 16/36G06F 40/211G06F 40/247G06F 40/253G06F 40/284

AI classification

Natural language1.00
Knowledge representation1.00
Machine learning1.00
Planning0.96
Speech0.18
AI hardware0.16
Vision0.02
Evolutionary computation0.00
© 2026 NYSGPT2525 LLC