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
Ownership
GOOGLE INC.
assignment · 297680013
Assignors
LERNER, URI N., JAHR, MICHAEL E.
On an employer assignment, the assignors are typically the inventors.