DETECTING AND EXECUTING DATA RE-INGESTION TO IMPROVE ACCURACY IN A NLP SYSTEM

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...

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Bibliographic Details
Main Authors CLARK ADAM T, HUEBERT JEFFREY K, PETRI JOHN E, DUBBELS JOEL C
Format Patent
LanguageEnglish
Published 18.09.2014
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary: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.
Bibliography:Application Number: US201313796562