TY - GEN
T1 - Automating the ILP setup task
T2 - Converting user advice about specific examples into general background knowledge
AU - Walker, Trevor
AU - O'Reilly, Ciaran
AU - Kunapuli, Gautam
AU - Natarajan, Sriraam
AU - MacLin, Richard
AU - Page, David
AU - Shavlik, Jude
PY - 2011
Y1 - 2011
N2 - Inductive Logic Programming (ILP) provides an effective method of learning logical theories given a set of positive examples, a set of negative examples, a corpus of background knowledge, and specification of a search space (e.g., via mode definitions) from which to compose the theories. While specifying positive and negative examples is relatively straightforward, composing effective background knowledge and search-space definition requires detailed understanding of many aspects of the ILP process and limits the usability of ILP. We introduce two techniques to automate the use of ILP for a non-ILP expert. These techniques include automatic generation of background knowledge from user-supplied information in the form of a simple relevance language, used to describe important aspects of specific training examples, and an iterative-deepening-style search process.
AB - Inductive Logic Programming (ILP) provides an effective method of learning logical theories given a set of positive examples, a set of negative examples, a corpus of background knowledge, and specification of a search space (e.g., via mode definitions) from which to compose the theories. While specifying positive and negative examples is relatively straightforward, composing effective background knowledge and search-space definition requires detailed understanding of many aspects of the ILP process and limits the usability of ILP. We introduce two techniques to automate the use of ILP for a non-ILP expert. These techniques include automatic generation of background knowledge from user-supplied information in the form of a simple relevance language, used to describe important aspects of specific training examples, and an iterative-deepening-style search process.
KW - Advice Taking
KW - Human Teaching of Machines
UR - https://www.scopus.com/pages/publications/79959290156
UR - https://www.scopus.com/pages/publications/79959290156#tab=citedBy
U2 - 10.1007/978-3-642-21295-6_28
DO - 10.1007/978-3-642-21295-6_28
M3 - Conference contribution
AN - SCOPUS:79959290156
SN - 9783642212949
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 253
EP - 268
BT - Inductive Logic Programming - 20th International Conference, ILP 2010, Revised Papers
PB - Springer Verlag
ER -