嵌入向量差异可以与不确定的内涵逻辑差异对齐
Embedding Vector Differences Can Be Aligned With Uncertain Intensional Logic Differences
摘要：
DeepWalk算法用于将嵌入向量分配给Atomspace加权的标记超图中的节点，该超图用于表示OpenCog AGI系统中的知识，应用于基于生物本体和基因组分析数据的长寿原因的概率推理。证明了在适当的条件下，嵌入向量间的向量差运算与嵌入向量所对应的超图节点间的“内涵差”运算是近似可等价的.这种关系暗示了不确定内涵逻辑和向量算术之间更广泛的函子映射，并为使用嵌入向量代数来指导内涵推理控制打开了大门。
英文摘要：
The DeepWalk algorithm is used to assign embedding vectors to nodes in the Atomspace weighted, labeled hypergraph that is used to represent knowledge in the OpenCog AGI system, in the context of an application to probabilistic inference regarding the causes of longevity based on data from biological ontologies and genomic analyses. It is shown that vector difference operations between embedding vectors are, in appropriate conditions, approximately alignable with "intensional difference" operations between the hypergraph nodes corresponding to the embedding vectors. This relationship hints at a broader functorial mapping between uncertain intensional logic and vector arithmetic, and opens the door for using embedding vector algebra to guide intensional inference control.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
