TY - GEN
T1 - Induction of logical relations based on specific generalization of strings
AU - Uzun, Yasin
AU - Cicekli, Ilyas
PY - 2007
Y1 - 2007
N2 - Learning logical relations from examples expressed as first order facts has been studied extensively by the Inductive Logic Programming research. Learning with positive-only data may cause over generalization of examples leading to inconsistent resulting hypotheses. A learning heuristic inferring specific generalization of strings based on unique match sequences is shown to be capable of learning predicates with string arguments. This paper describes an inductive learner based on the idea of specific generalization of strings, and the given clauses are generalized by considering the background knowledge.
AB - Learning logical relations from examples expressed as first order facts has been studied extensively by the Inductive Logic Programming research. Learning with positive-only data may cause over generalization of examples leading to inconsistent resulting hypotheses. A learning heuristic inferring specific generalization of strings based on unique match sequences is shown to be capable of learning predicates with string arguments. This paper describes an inductive learner based on the idea of specific generalization of strings, and the given clauses are generalized by considering the background knowledge.
UR - http://www.scopus.com/inward/record.url?scp=48649088973&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48649088973&partnerID=8YFLogxK
U2 - 10.1109/ISCIS.2007.4456855
DO - 10.1109/ISCIS.2007.4456855
M3 - Conference contribution
AN - SCOPUS:48649088973
SN - 1424413648
SN - 9781424413645
T3 - 22nd International Symposium on Computer and Information Sciences, ISCIS 2007 - Proceedings
SP - 163
EP - 168
BT - 22nd International Symposium on Computer and Information Sciences, ISCIS 2007 - Proceedings
T2 - 22nd International Symposium on Computer and Information Sciences, ISCIS 2007
Y2 - 7 November 2007 through 9 November 2007
ER -