Selectively merging clusters of conceptually related words in a generative model for text
US9507858B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 27, 2012 |
| Grant date | Nov 29, 2016 |
| Priority date | — |
| Expiry date | Jul 25, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/38
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.