Method of automated discovery of new topics
US9177262B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 2, 2014 |
| Grant date | Nov 3, 2015 |
| Priority date | — |
| Expiry date | Dec 2, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to a method for performing automated discovery of new topics from unlimited documents related to any subject domain, employing a multi-component extension of Latent Dirichlet Allocation (MC-LDA) topic models, to discover related topics in a corpus. The resulting data may contain millions of term vectors from any subject domain identifying the most distinguished co-occurring topics that users may be interested in, for periodically building new topic ID models using new content, which may be employed to compare one by one with existing model to measure the significance of changes, using term vectors differences with no correlation with a Periodic New Model, for periodic updates of automated discovery of new topics, which may be used to build a new topic ID model in-memory database to allow query-time linking on massive data-set for automated discovery of new topics.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.