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

IPC: G06F40/35 ,  G06F16/33 ,  G06N5/04

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.

公开(公告)号：US20210297498A1

公开(公告)日：2021-09-23

申请号：US17191698

申请日：2021-03-04

Applicant: SRI International

Inventor： Ajay Divakaran ,  Karan Sikka ,  Arijit Ray ,  Xiao Lin ,  Yi Yao

IPC: H04L29/08

Abstract: A method, apparatus and system for determining user-content associations for determining and providing user-preferred content using multimodal embeddings include creating an embedding space for multimodal content by creating a first modality vector representation of the multimodal content having a first modality, creating a second modality vector representation of the multimodal content having a second modality, creating a user vector representation, as a third modality, for each user associated with at least a portion of the multimodal content, and embedding the first and the second modality vector representations and the user vector representations in the common embedding space using at least a mixture of loss functions for each modality pair of the first, the at least second and the third modalities that pushes closer co-occurring pairs of multimodal content. Embodiments can further include generating content using determined attributes of a message to be conveyed and features of the user-preferred content.