This book constitutes the strictly refereed post-workshop proceedings of the 6th International Workshop on Inductive Logic Programming, ILP-96, held in Stockholm, Sweden, in August 1996.
Ontology learning is an interdisciplinary research field drawing on techniques from Formal Concept Analysis [13,14], Natural Language Processing [15,16] and machine learning [6,16,17], to name a few. One classification of ontology ...
Wiley, New York (1994) 5. Bohan, D.A., Caron-Lormier, G., Muggleton, S.H., Raybould, A., TamaddoniNezhad, A.: Automated discovery of food webs from ecological data using logicbased machine learning. PloS ONE 6(12), ...
Although the classification accuracy achieved in this paper is still inferior to the state of the art of NN technologies,6 the current paper shows potentials of symbolic reasoning for feature learning from raw data.
Plotkin , G. D .: A further note on inductive generalization . In B. Meltzer and D. Michie ( Eds . ) : Machine Intelligence 6. Elsevier , New York ( 1971 ) 6. Quinlan , J. R .: Learning Logical Definitions from Relations .
Kersting and De Raedt [12] discuss a gradient-based method to solve the same problem for Bayesian logic programs. Friedman et al. [6,7] tackle the problem of learning the logical structure of first order probabilistic models.
6 Conclusions We presented initial results on machine learning of general predictive models from ecological data. We have considered two different but related directions to extend our previous approach for machine learning of food-webs: ...
Parameter estimation in stochastic logic programs. ... 6. S. Muggleton. Inverse entailment and Progol. New Generation Computing, 13:245– 286, 1995. 7. S. Muggleton. Inductive logic programming: ... Learning stochastic logic programs.
Essentials of Logic Programming. Oxford University Press, 1990. 14. S.-H. Nienhuys-Cheng and R. de Wolf. Foundations of Inductive Logic Programming, volume 1228 of Lecture Notes in Artificial Intelligence. Springer-Verlag, 1997. 15.
... C.J.: Essentials of logic programming. Oxford University Press, New York (1990) 4. Heras, F., Larrosa, J., Oliveras, A.: MINIMAXSAT: an efficient weighted max-SAT solver. Journal of Artificial Intelligence Research 31(1), ...
In this book they provide an extended, up-to-date survey of ILP, emphasizing methods and systems suitable for software engineering applications, including inductive program development, testing, and maintenance.
This book describes the theory, implementations and applications of Inductive Logic Programming.
This book constitutes the strictly refereed post-workshop proceedings of the 6th International Workshop on Inductive Logic Programming, ILP-96, held in Stockholm, Sweden, in August 1996.
Inductive Logic Programming: Techniques and Applications
This book constitutes the refereed conference proceedings of the 29th International Conference on Inductive Logic Programming, ILP 2019, held in Plovdiv, Bulgaria, in September 2019.
This book constitutes the refereed conference proceedings of the 28th International Conference on Inductive Logic Programming, ILP 2018, held in Ferrara, Italy, in September 2018.
This book constitutes the refereed proceedings of the 13th International Conference on Inductive Logic Programming, ILP 2003, held in Szeged, Hungary in September/October 2003.
This book constitutes the thoroughly refereed post-conference proceedings of the 17th International Conference on Inductive Logic Programming, ILP 2007, held in Corvallis, OR, USA, in June 2007 in conjunction with ICML 2007, the ...
This book constitutes the refereed proceedings of the 10th International Conference on Inductive Logic Programming, ILP 2000, held in London, UK in July 2000 as past of CL 2000.
Wewishtothank AlfredHofmannandAnnaKramerofSpringer-Verlagfortheircooperationin publishing these proceedings. Finally, we gratefully acknowledge the nancial supportprovidedbythesponsorsofILP-99.