DocumentCode
2698570
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
fYear
2009
fDate
1-3 April 2009
Firstpage
214
Lastpage
219
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ACIIDS.2009.40
Filename
5175995
Link To Document