Approaches to Parallel Graph-Based Knowledge Discovery

Journal of Parallel and Distributed Computing

Volumn 61, Issue 3, 2001, Pages 427-446

  Cook, Diane J ^a   Holder, Lawrence B ^a   Galal, Gehad ^a   Maglothin, Ron ^a  

^a The University of Texas at Arlington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0012186914     PISSN: 07437315     EISSN: None     Source Type: Journal    
DOI: 10.1006/jpdc.2000.1696     Document Type: Article

References (29)

1. Asker L., Maclin R. Ensembles as a sequence of classifiers. Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. 1997.
2. Chan P., Stolfo S. Toward parallel and distributed learning by meta-learning. Working Notes of the AAAAI-93 Workshop on Knowledge Discovery in Databases. 1993;. p. 227-240.
3. Cheeseman P., Stutz J. Bayesian classification (AutoClass): Theory and results. Fayyad U. M., Piatetsky-Shapiro G., Smyth P., Uthurusamy R. Advances in Knowledge Discovery and Data Mining. 1996;153-180 MIT Press, Cambridge.
4. Clearwater S., Provost F. A tool for knowledge-based introduction. Proceedings of the Second International IEEE Conference on Tools for Artificial Intelligence. 1990;. p. 24-30.
5. Conklin D., Glasgow J. Spatial analogy and subsumption. Proceedings of the Machine Learning Conference. 1992;. p. 111-116.
6. Cook D. J., Holder L. B. Substructure discovery using minimum description length and background knowledge. J. Artificial Intelligent Res. 1:1994;231-255.
7. D. J. Cook, and, L. B. Holder, Graph-based data mining, IEEE Intelligent Systems, in press.
8. Cook D. J., Holder L. B., Djoko S. Scalable discovery of informative structural concepts using domain knowledge. IEEE Expert. 10:1996;59-68.
9. Cook D. J., Varnell R. C. Maximizing the benefits of parallel search using machine learning. Proceedings of the National Conference on Artificial Intelligence. 1997.
10. Cook D. J., Varnell R. C. Adaptable incremental deepening search. J. Artificial Intelligence Research. 1998.
11. Djoko S. The Role of Domain Knowledge in Substructure Discovery. Aug. 1995;University of Texas at ArlingtonDepartement of Computer Science and Engineering.
12. Djoko S., Cook D. J., Holder L. B. Analyzing the benefits of domain knowledge in substructure discovery. Proceedings of the First International Conference on Knowledge Discovery and Data Mining. 1995;. p. 75-80.
13. Fayyad U. M., Piatetsky-Shapiro G., Smyth P. From data mining to knowledge discovery: An overview. Fayyad U. M., Piatetsky-Shapiro G., Smyth P., Uthurusamy R. Advances in Knowledge Discovery and Data Mining. 1996;1-34 MIT Press, Cambridge.
14. Fayyad U. M., Piatetsky-Shapiro G., Smyth P., Uthurusamy R. Advances in Knowledge Discovery and Data Mining. 1996;AAAI Press, Menlo Park.
15. Fishere D. Knowledge acquisition via incremental conceptual clustering. Machine Learning. 2:1987;139-172.
16. Geist A., Beguelin A., Dongarra J., Jiang W., Manchek R., Sunderam V. PVM: Parallel Virtual Machine, A User's guide and Tutorial for Networked Parallel Computing. 1994;MIT Press, Cambridge.
17. Karypis G., Kumar V. Multilevel k-way partitioning scheme for irregular graphs. J. Parallel Distrib. Comput. 48:1998;96-129.
18. Kumar V., Rao V. N. Scalable parallel formulations of depth-first search. Kumar, Kanal, Gopalakrishan. Parallel Algorithms for Machine Intelligence and Vision. 1990;1-41 Springer-Verlag, Berlin/New York.
19. Levinson R. A self-organizing retrieval system of graphs. Proceedings of the National Conference on Artificial Intelligence. 1984;. p. 203-206.
20. Potts J. T. Technical Report. 1996.
21. Powley C., Ferguson C., Korf R. E. Parallel heuristic search: Two approaches. Kumar, Kanal, Gopalakrishan. Parallel Algorithms for Machine Intelligence and Vision. 1990;Springer-Verlag, Berlin/New York.
22. Provost F. J., Buchanan B. G., Clearwater S. H., Lee Y. Technical Report. 1993.
23. Provost F. J., Hennessy D. Scaling up: Distributed machine learning with cooperation. Proceedings of the Thirteenth National Conference on Artificial Intelligence. 1996;. p. 74-79.
24. Rissanen J. Stochastic Complexity in Statistical Inquiry. 1989;World Scientific, Singapore.
25. Segen J. Graph clustering and model learning by data compression. Proceedings of the Machine Learning Conference. 1990;. p. 93-101.
26. Shaw M. J., Sikora R. Technical Report. 1990.
27. Su S., Cook D. J., Holder L. B. Application of knowledge discovery to molecular biology: Identifying structural regularities in proteins. Proceedings of the Pacific Symposium on Biocomputing. 1999;. p. 190-201.
28. Thompson K., Langley P. Concept formation in structured domains. Fisher D. H., Pazzani M. Concept Formation: Knowledge and Experience in Unsupervised Learning. 1991;Morgan Kaufmann, San Mateo.
29. Yoshida K., Motoda H., Indurkhya N. Unifying learning methods by colored digraphs. Proceedings of the Learning and Knowledge Acquisition Workshop at IJCAI-93. 1993.