Method For Recommending Content To Ingest As Corpora Based On Interaction History In Natural Language Question And Answering Systems

摘要

An approach is provided for generating actionable content ingestion recommendations based on an interaction history that is mined to extract interaction context parameters from questions and answer results that meet specified answer deficiency criteria by searching one or more content sources using the extracted interaction context parameters to identify new content that is relevant to improving the first answer, and then presenting the new content in an actionable content ingestion recommendation list for display and review by a domain expert, where the actionable content ingestion recommendation list recommends the new content for ingestion in a knowledge base corpus.

主权项

1. A method of generating actionable content ingestion recommendations, the method comprising:
mining, by an information handling system comprising a processor and a memory, an interaction history comprising a plurality of questions and answer results for a plurality of users to extract interaction context parameters for at least a first answer that meets specified answer deficiency criteria; searching, by the information handling system, one or more content sources using the extracted interaction context parameters along with multi-factorial variable or attributes about the users to identify new content that is relevant to improving the first answer or adding new answers to a candidate answer list; and presenting, by the information handling system, an actionable content ingestion recommendation for display and review by a domain expert, where the actionable content ingestion recommendation lists the new content for ingestion in a knowledge base corpus.