LANGUAGE INDEPENDENT REPRESENTATIONS

Patent №

US 10,671,816

Granted

2020-06-02

Filed 2018

Owner

Lab

AI components

5

ml · nlp · vision · kr · hardware

Assignment

None on record

Dataset

AIPD

2023_r1 edition

Application

15968983

Snippets can be represented in a language-independent semantic manner. Each portion of a snippet can be represented by a combination of a semantic representation and a syntactic representation, each in its own dimensional space. A snippet can be divided into portions by constructing a dependency structure based on relationships between words and phrases. Leaf nodes of the dependency structure can be assigned: A) a semantic representation according to pre-defined word mappings and B) a syntactic representation according to the grammatical use of the word. A trained semantic model can assign to each non-leaf node of the dependency structure a semantic representation based on a combination of the semantic and syntactic representations of the corresponding lower-level nodes. A trained syntactic model can assign to each non-leaf node a syntactic representation based on a combination of the syntactic representations of the corresponding lower-level nodes and the semantic representation of that node.

AI classification

Natural language1.00
AI hardware1.00
Machine learning1.00
Knowledge representation1.00
Vision0.91
Speech0.30
Evolutionary computation0.00
Planning0.00
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