Login: A logic programming language with built-in inheritance
Journal of Logic Programming
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
The logic of typed feature structures
The logic of typed feature structures
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Induction of Feature Terms With INDIE
ECML '97 Proceedings of the 9th European Conference on Machine Learning
Cases as terms: A feature term approach to the structured representation of cases
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Learning information extraction patterns from examples
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
University of Massachusetts: MUC-4 test results and analysis
MUC4 '92 Proceedings of the 4th conference on Message understanding
RHB+: a type-oriented ILP system learning from positive data
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
CRYSTAL inducing a conceptual dictionary
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Automatically generating extraction patterns from untagged text
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
| Hi-index | 0.00 |
This paper extends the traditional inductive logic programming (ILP) framework to a ψ-term capable ILP framework. Aït-Kaci's ψ-terms have interesting and significant properties for markedly widening applicable areas of ILP. For example, ψ-terms allow partial descriptions of information, generalization and specialization of sorts (or types) placed instead of function symbols, and abstract descriptions of data using sorts; they have comparable representation power to feature structures used in natural language processing. We have developed an algorithm that learns logic programs based on ψ-terms, made possible by a bottom-up approach employing the least general generalization (lgg) extended for ψ-terms. As an area of application, we have selected information extraction (IE) tasks in which sort information is crucial in deciding the generality of IE rules. Experiments were conducted on a set of test examples and background knowledge consisting of case frames of newspaper articles. The results showed high precision and recall rates for learned rules for the IE tasks.