知识图谱的拓展及其智能拓展库

Extension of Knowledge Graph and its Intelligent Extension Library

知识图谱发展的终极目标是要把数据库构建成为人脑知识生长的同构体,它不是被动的僵化储存所,而是主动生长的拓展体。本文提出了智能拓展库的构想,它是知识图谱的升级版,也是一个多层次的嵌入式图数据库系统。每个概念节点都是一个窗口,打开窗口即生成一个子库。所有概念都按层次编码,可快捷查询。一个概念节点称为花苞,如果该概念的多个因素都以它为定义域,则打开花苞的窗口,就是一张因果分析表,用因素空间理论可以回答智能判断、推理、评价、决策、规划等一系列问题,使数据库成为智能孵化生长的活体。本文建立的智能拓展库语言有可能用于机制主义通用人工智能理论,并开展智能孵化的全民工程。

The ultimate goal of constructing the database of the knowledge graph should be the isomorphism of human brain knowledge growth,and it should not be a passive solidified storage body but an actively growing hatching body.The idea of intelligent reproduction library is proposed,which is an updated version of the Knowledge graph,a multi-level embedded graph database system.Each concept node is a window.Open the window,and there is a sub-library produced.All concepts are coded hierarchically for fast query.A concept node is called a bud if the concept has multiple factors taking it as domain.Open the window of the bud,and a cause and effect analysis table is prepared,on which,factor space theory can perform algorithms to make intelligent judgment,reasoning,evaluation,decision-making and planning,by which the database becomes a living intelligent incubator.The Factorial Query Language(FQL)is also established,which may be used in the preparation of the intelligent incubation civil intelligent engineering,with guidance of the mechanistic general artificial intelligence theory.