Empirical Substructure Discovery

Holder, Lawrence B.

doi:10.1016/B978-1-55860-036-2.50041-2

Empirical Substructure Discovery

Lawrence B. Holder

ICML 1989 pp. 133-136

doi:10.1016/B978-1-55860-036-2.50041-2 /icml/1989/holder1989icml-empirical/

Abstract

This paper describes the substructure discovery method used in the SUBDUE system. The method involves a computationally constrained best-first search guided by four heuristics: cognitive savings, compactness, connectivity and coverage. Each of the four heuristics are described along with their role in the evaluation of a substructure. An example demonstrates SUBDUE's ability to discover substructure and the advantages to be gained by other learning systems from the discovery of substructure concepts.

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Cite

Text

Holder. "Empirical Substructure Discovery." International Conference on Machine Learning, 1989. doi:10.1016/B978-1-55860-036-2.50041-2

Markdown

[Holder. "Empirical Substructure Discovery." International Conference on Machine Learning, 1989.](https://mlanthology.org/icml/1989/holder1989icml-empirical/) doi:10.1016/B978-1-55860-036-2.50041-2

BibTeX

@inproceedings{holder1989icml-empirical,
  title     = {{Empirical Substructure Discovery}},
  author    = {Holder, Lawrence B.},
  booktitle = {International Conference on Machine Learning},
  year      = {1989},
  pages     = {133-136},
  doi       = {10.1016/B978-1-55860-036-2.50041-2},
  url       = {https://mlanthology.org/icml/1989/holder1989icml-empirical/}
}