Deductive and Analogical Reasoning on a Semantically Embedded Knowledge Graph

被引：2
作者：
Summers-Stay, Douglas [1 ]
机构：
[1] US Army, Res Lab, Adelphi, MD 20783 USA
来源：
ARTIFICIAL GENERAL INTELLIGENCE: 10TH INTERNATIONAL CONFERENCE, AGI 2017 | 2017年 / 10414卷
关键词：
Semantic vectors; Reasoning; Knowledge graphs; Knowledge bases; Analogy;
D O I：
10.1007/978-3-319-63703-7_11
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Representing knowledge as high-dimensional vectors in a continuous semantic vector space can help overcome the brittleness and incompleteness of traditional knowledge bases. We present a method for performing deductive reasoning directly in such a vector space, combining analogy, association, and deduction in a straightforward way at each step in a chain of reasoning, drawing on knowledge from diverse sources and ontologies.
引用
收藏
页码：112 / 122
页数：11
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