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公开(公告)号:US11934793B2
公开(公告)日:2024-03-19
申请号:US17516409
申请日:2021-11-01
Applicant: SRI International
Inventor: Ajay Divakaran , Karan Sikka , Yi Yao , Yunye Gong , Stephanie Nunn , Pritish Sahu , Michael A. Cogswell , Jesse Hostetler , Sara Rutherford-Quach
CPC classification number: G06F40/35 , G06F16/3335 , G06N5/04
Abstract: A method, apparatus and system for training an embedding space for content comprehension and response includes, for each layer of a hierarchical taxonomy having at least two layers including respective words resulting in layers of varying complexity, determining a set of words associated with a layer of the hierarchical taxonomy, determining a question answer pair based on a question generated using at least one word of the set of words and at least one content domain, determining a vector representation for the generated question and for content related to the at least one content domain of the question answer pair, and embedding the question vector representation and the content vector representations into a common embedding space where vector representations that are related, are closer in the embedding space than unrelated embedded vector representations. Requests for content can then be fulfilled using the trained, common embedding space.