Acquisition of Terminological Knowledge in Probabilistic Description Logic

被引:1
作者
Kriegel, Francesco [1 ]
机构
[1] Tech Univ Dresden, Inst Theoret Comp Sci, Dresden, Germany
来源
KI 2018: ADVANCES IN ARTIFICIAL INTELLIGENCE | 2018年 / 11117卷
关键词
Data mining; Knowledge acquisition; Probabilistic description logic; Knowledge base; Probabilistic interpretation; Concept inclusion;
D O I
10.1007/978-3-030-00111-7_5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
For a probabilistic extension of the description logic epsilon L-perpendicular to,L- we consider the task of automatic acquisition of terminological knowledge from a given probabilistic interpretation. Basically, such a probabilistic interpretation is a family of directed graphs the vertices and edges of which are labeled, and where a discrete probability measure on this graph family is present. The goal is to derive so-called concept inclusions which are expressible in the considered probabilistic description logic and which hold true in the given probabilistic interpretation. A procedure for an appropriate axiomatization of such graph families is proposed and its soundness and completeness is justified.
引用
收藏
页码:46 / 53
页数:8
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