Identifying a stale data source to improve NLP accuracy
US10387468B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 14, 2013 |
| Grant date | Aug 20, 2019 |
| Priority date | — |
| Expiry date | Nov 29, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In some NLP systems, queries are compared to different data sources stored in a corpus to provide an answer to the query. However, the best data sources for answering the query may not currently be contained within the corpus or the data sources in the corpus may contain stale data that provides an inaccurate answer. When receiving a query, the NLP system may evaluate the query to identify a data source that is likely to contain an answer to the query. If the data source is not currently contained within the corpus, the NLP system may ingest the data source. If the data source is already within the corpus, however, the NLP may determine a time-sensitivity value associated with at least some portion of the query. This value may then be used to determine whether the data source should be re-ingested—e.g., the information contained in the corpus is stale.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.