SELECTIVELY MERGING CLUSTERS OF CONCEPTUALLY RELATED WORDS IN A GENERATIVE MODEL FOR TEXT

Patent №

US 9,507,858

Granted

2016-11-29

Filed 2012

Owner

GOOGLE INC.

AI components

6

ml · nlp · speech · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

13686781

One embodiment of the present invention provides a system that merges similar clusters of conceptually-related words in a probabilistic generative model for textual documents. During operation, the system receives a current model, which contains terminal nodes representing random variables for words and contains cluster nodes representing clusters of conceptually related words. Nodes in the current model are coupled together by weighted links, wherein if a node fires, a link from the node to another node causes the other node to fire with a probability proportionate to the weight of the link. Next, the system determines whether cluster nodes in the current model explain other cluster nodes in the current model. If two cluster nodes explain each other, the system merges the two cluster nodes to form a combined cluster node.

AI classification

Natural language1.00
Machine learning1.00
Planning1.00
Knowledge representation1.00
AI hardware0.94
Speech0.84
Vision0.00
Evolutionary computation0.00

Ownership

GOOGLE INC.

assignment · 297680013

Assignors

LERNER, URI N., JAHR, MICHAEL E.

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

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