Topic specific language models built from large numbers of documents
US7739286B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 17, 2006 |
| Grant date | Jun 15, 2010 |
| Priority date | — |
| Expiry date | Jan 23, 2027 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/183
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Forming and/or improving a language model based on data from a large collection of documents, such as web data. The collection of documents is queried using queries that are formed from the language model. The language model is subsequently improved using the information thus obtained. The improvement is used to improve the query. As data is received from the collection of documents, it is compared to a rejection model, that models what rejected documents typically look like. Any document that meets the test is then rejected. The documents that remain are characterized to determine whether they add information to the language model, whether they are relevant, and whether they should be independently rejected. Rejected documents are used to update the rejection model; accepted documents are used to update the language model. Each iteration improves the language model, and the documents may be analyzed again using the improved language model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.