Exact Learning of Light weight Description Logic Ontologies

被引:0
作者
Konev, Boris [1 ]
Lutz, Carsten [2 ]
Ozaki, Ana [3 ]
Wolter, Frank [1 ]
机构
[1] Univ Liverpool, Dept Comp Sci, Liverpool, Merseyside, England
[2] Univ Bremen, Dept Comp Sci, Bremen, Germany
[3] Tech Univ Dresden, Dept Comp Sci, Dresden, Germany
基金
英国工程与自然科学研究理事会;
关键词
Exact Learning; Description Logic; Complexity; DL-LITE FAMILY; HORN EXPRESSIONS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We study the problem of learning description logic (DL) ontologies in Angluin et al.'s framework of exact learning via queries. We admit membership queries ("is a given subsumption entailed by the target ontology?") and equivalence queries ("is a given ontology equivalent to the target ontology?"). We present three main results: (1) ontologies formulated in (two relevant versions of) the description logic DL-Lite can be learned with polynomially many queries of polynomial size; (2) this is not the case for ontologies formulated in the description logic epsilon L, even when only acyclic ontologies are admitted; and (3) ontologies formulated in a fragment of epsilon L related to the web ontology language OWL 2 RL can be learned in polynomial time. We also show that neither membership nor equivalence queries alone are sufficient in cases (1) and (3).
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页数:63
相关论文
共 64 条
[1]   NEGATIVE RESULTS FOR EQUIVALENCE QUERIES [J].
ANGLUIN, D .
MACHINE LEARNING, 1990, 5 (02) :121-150
[2]  
ANGLUIN D, 1992, MACH LEARN, V9, P147, DOI 10.1007/BF00992675
[3]  
Angluin D., 1987, MACH LEARN, V2, P319
[4]  
Angluin Dana, 1987, TECHNICAL REPORT
[5]  
[Anonymous], 2003, DESCRIPTION LOGIC HD
[6]  
[Anonymous], 2014, THESIS
[7]  
[Anonymous], 2016, CONCEPTUAL EXPLORATI, DOI DOI 10.1007/978-3-662-49291-8
[8]   Learning closed Horn expressions [J].
Arias, M ;
Khardon, R .
INFORMATION AND COMPUTATION, 2002, 178 (01) :214-240
[9]  
Arias M., 2004, THESIS
[10]  
Arias M, 2007, J MACH LEARN RES, V8, P549