Abstract
Several learning systems, such as systems based on clustering and instance based learning, use a measure of distance between objects. Good measures of distance exist when objects are described by a fixed set of attributes as in attribute value learners. More recent learning systems however, use a first order logic representation. These systems represent objects as models or clauses. This paper develops a general framework for distances between such objects and reports a preliminary evaluation.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
G. Bisson. Conceptual clustering in a first order logic representation. In Proceedings of the 10th European Conference on Artificial Intelligence, pages 458–462. John Wiley & Sons, 1992.
H. Blockeel and L. De Raedt. Top-down induction of first order logical decision trees. Artificial Intelligence, 1998. To appear.
H. Blockeel, L. De Raedt, and J. Ramon. Top-down induction of clustering trees. In Proceedings of the 15th International Conference on Machine Learning, 1998.
L. De Raedt. Logical settings for concept learning. Artificial Intelligence, 95:187–201, 1997.
L. De Raedt and L. Dehaspe. Clausal discovery. Machine Learning, 26:99–146, 1997.
L. De Raedt and S. Dieroski. First order j k-Causal theories are PAC-learnable. Artificial Intelligence, 70:375–392, 1994.
L. De Raedt and W. Van Laer. Inductive constraint logic. In Proceedings of the 5th Workshop on Algorithmic Learning Theory, volume 997 of Lecture Notes in Artificial Intelligence. Springer-Verlag, 1995.
S. Džeroski, S. Schulze-Kremer, K. R. Heidtke, K. Siems, D. Wettschereck, and H. Blockeel. Diterpene structure elucidation from 13C NMR spectra with inductive logic programming. Applied Artificial Intelligence. Special Issue on First-Order Knowledge Discovery in Databases, 1998. To appear.
T. Eiter and Mannila H. Distance measures for point sets and their computation. Acta Informatica, 34, 1997.
W. Emde and D. Wettschereck. Relational instance based learning. In Proceedings of the 1995 Workshop of the GI Special Interest Group on Machine Learning, 1995.
A. Hutchinson. Metrics on terms and clauses. In Proceedings of the 9th European Conference on Machine Learning, Lecture Notes in Artificial Intelligence, pages 138–145. Springer-Verlag, 1997.
P. Langley. Elements of Machine Learning. Morgan Kaufmann, 1996.
Shan-Hwei Nienhuys-Cheng. Distance between herbrand interpretations: A measure for approximations to a target concept. In Proceedings of the 7th International Workshop on Inductive Logic Programming, Lecture Notes in Artificial Intelligence. Springer-Verlag, 1997.
J. Ramon and M. Bruynooghe. A framework for defining distances between first-order logic objects. Technical Report CW 263, Department of Computer Science, Katholieke Universiteit Leuven, 1998. http: //www. cs. kuleuven. ac. be/-publicaties/rapporten/CW1998.htm1.
J. Ramon, M. Bruynooghe, and W. Van Laer. Distance measures between atoms. Technical Report CW 264, Department of Computer Science, Katholieke Universiteit Leuven, 1998. http://www.cs.kuleuven.ac.be/publicaties/rapporten/-CW1998.htm1.
A. Srinivasan, S.H. Muggleton, R.D. King, and M.J.E. Sternberg. Mutagenesis: ILP experiments in a non-determinate biological domain. In S. Wrobel, editor, Proceedings of the 4th International Workshop on Inductive Logic Programming, volume 237 of GMD-Studien, pages 217–232. Gesellschaft für Mathematik und Datenverarbeitung MBH, 1994. *** DIRECT SUPPORT *** A0008D21 00009
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ramon, J., Bruynooghe, M. (1998). A framework for defining distances between first-order logic objects. In: Page, D. (eds) Inductive Logic Programming. ILP 1998. Lecture Notes in Computer Science, vol 1446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027331
Download citation
DOI: https://doi.org/10.1007/BFb0027331
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64738-6
Online ISBN: 978-3-540-69059-7
eBook Packages: Springer Book Archive