Title :
Extensions to the Relational Paths Based Learning Approach RPBL
Author :
Gao, Zhiqiang ; Zhang, Zhizheng ; Huang, Zhisheng
Author_Institution :
Inst. of Comput. Sci. & Eng., Southeast Univ., Nanjing, China
Abstract :
In this paper we extend RPBL, a Relational Paths Based Learning approach for first order theories in three directions. We apply domain theories to expand structured instance space, learn recursive theories by an example of learningmember relationship of lists, and analyze the performance as well as time complexity theoretically. In addition, we give the details of our experimental results.
Keywords :
inductive logic programming; learning (artificial intelligence); learning by example; Inductive logic programming; domain theories; learning by example; recursive theories; relational paths based learning approach; structured instance space; time complexity; Computer science; Data engineering; Database systems; Deductive databases; Explosions; Law; Learning systems; Legal factors; Logic programming; Performance analysis; inductive logic programming; machine learning;
Conference_Titel :
Intelligent Information and Database Systems, 2009. ACIIDS 2009. First Asian Conference on
Conference_Location :
Dong Hoi
Print_ISBN :
978-0-7695-3580-7
DOI :
10.1109/ACIIDS.2009.40
