DocumentCode :
2070804
Title :
Data flow coherence criteria in ILP tools
Author :
Muresan, Smaranda ; Muresan, Tudor ; Potolea, Rodica
Author_Institution :
Dept. of Comput. Sci., Columbia Univ., New York, NY, USA
fYear :
2001
fDate :
7-9 Nov 2001
Firstpage :
179
Lastpage :
186
Abstract :
In this paper we present a new method that uses data flow coherence criteria in definite logic program generation. We outline three main advantages of these criteria supported by our results: (i) drastically pruning the search space (around 90%), (ii) reducing the set of positive examples and reducing or even removing the need for the set of negative examples, and (iii) allowing the induction of predicates that are difficult or even impossible to generate by other methods. Besides these criteria, the approach takes into consideration the program termination condition for recursive predicates. The paper outlines some theoretical issues and implementation aspects of our system for automatic logic program induction
Keywords :
data flow computing; data mining; inductive logic programming; learning (artificial intelligence); search problems; ILP tools; automatic logic program induction; data flow coherence criteria; definite logic program generation; inductive logic programming; program termination condition; recursive predicates; search space; Automatic logic units; Benchmark testing; Computer science; Induction generators; Lattices; Logic programming; Machine learning; Machine learning algorithms; Magnetic heads; Natural language processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, Proceedings of the 13th International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
0-7695-1417-0
Type :
conf
DOI :
10.1109/ICTAI.2001.974463
Filename :
974463
Link To Document :
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