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SOCIAL NETWORK ANALYSIS WITH PRIOR KNOWLEDGE AND NON-NEGATIVE TENSOR FACTORIZATION

机译:具有先验知识和非负张量化的社会网络分析

摘要

Systems and methods are disclosed to analyze a social network by generating a data tensor from social networking data; applying a non-negative tensor factorization (NTF) with user prior knowledge and preferences to generate a core tensor and facet matrices; and rendering information to social networking users based on the core tensor and facet matrices.
机译:公开了通过从社交网络数据生成数据张量来分析社交网络的系统和方法。应用具有用户先验知识和偏好的非负张量因子分解(NTF)来生成核心张量和构面矩阵;并基于核心张量和构面矩阵将信息呈现给社交网络用户。

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