arrow
返回

Analogy between concepts

delete2019-10-01
delete24
delete
OA
AI
N
Nelly Barbot *
L
Laurent Miclet
H
Henri Prade
DOI:10.1016/j.artint.2019.06.008delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Reasoning by analogy plays an important role in human thinking, in exploring parallels between situations. It enables us to explain by comparing, to draw plausible conclusions, or to create new devices or concepts by transposing old ones in new contexts. A basic form of analogy, called Analogical Proportion (AP), describes a particular relation between four objects of the same kind, e.g. A calf is to a bull as a foal is to a stallion. It is only recently that researchers have started to study APs in a formal way and to use their properties in different tasks of artificial intelligence (AI). This paper follows this line of research. Specifically, we are interested in giving the definition and some properties of an AP in lattices, a widely used structure in AI. We give general results before focusing on Concept Lattices, with the goal to investigate how analogical reasoning could be introduced in the framework of Formal Concept Analysis (FCA). This leads us to define an AP between formal concepts and to give algorithms to compute them, but also to point to special subcontexts, called analogical complexes. They are themselves organized as a lattice, and we show that they are closely related to APs between concepts, while not needing the complete construction of the lattice. To finish, we relate them to another form of analogy, called Relational Proportion, which involves two universes of discourse, e.g. Carlsen is to chess as Mozart is to music, which leads to the more compact way of saying Carlsen is the Mozart of chess, which is not anymore a relation between four objects of the same kind, but can be interpreted as well in FCAs framework. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Analogy
Analogical reasoning
Analogical proportion
Analogy in lattices
Formal concept analysis
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Artificial Intelligence Review 封面图
Artificial Intelligence Review
IF:
13.9
论文数:
6.1K
被引数:
1.9W

机构

C
centre national de la recherche scientifique (cnrs)
学者数:
24.5W
论文数: 18.2W
被引数: 279
U
universite de toulouse
学者数:
3.5W
论文数: 2.7W
被引数: 37