TY - GEN
T1 - Learning terminologies in probabilistic description logics
AU - Revoredo, Kate
AU - Ochoa-Luna, José Eduardo
AU - Cozman, Fabio Gagliardi
PY - 2010/1/1
Y1 - 2010/1/1
N2 - This paper investigates learning methods where the target language is the recently proposed probabilistic description logic cr . We start with an inductive logic programming algorithm that learns logical constructs; we then develop an algorithm that learns probabilistic constructs by searching for conditioning concepts, using examples given as interpretations. Issues on learning from entailments are also examined, and practical examples are discussed. © 2010 Springer-Verlag.
AB - This paper investigates learning methods where the target language is the recently proposed probabilistic description logic cr . We start with an inductive logic programming algorithm that learns logical constructs; we then develop an algorithm that learns probabilistic constructs by searching for conditioning concepts, using examples given as interpretations. Issues on learning from entailments are also examined, and practical examples are discussed. © 2010 Springer-Verlag.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78649940953&origin=inward
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=78649940953&origin=inward
U2 - 10.1007/978-3-642-16138-4_5
DO - 10.1007/978-3-642-16138-4_5
M3 - Conference contribution
SN - 3642161375
SN - 9783642161377
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 41
EP - 50
BT - Learning terminologies in probabilistic description logics
T2 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Y2 - 1 January 2018
ER -