Databases Reference
In-Depth Information
11. Coenen F, Goulbourne G, Leng P (2001) Computing association rules using
partial totals. In: Raedt LD, Siebes A (eds): Principles of Data Mining and
Knowledge Discovery - Proceedings of the 5th European Conference on Prin-
ciples and Practice of Knowledge Discovery in Databases (PKDD-01, Springer,
Berlin Heidelberg New York), Freiburg, Germany, September 2001. (LNAI 2168,
ISBN 3-540-42534-9, pages 54-66)
12. Coenen F, Leng P (2001) Optimising association rule algorithms using itemset
ordering. In: Bramer M, Coenen F, Preece A (eds): Research and Develop-
ment in Intelligent Systems XVIII - Proceedings of the Twenty-first SGES
International Conference on Knowledge Based Systems and Applied Artificial
Intelligence (ES-01, Springer, Berlin Heidelberg New York), Cambridge, United
Kingdom, December 2001. (ISBN 1852335351, pages 53-66)
13. Coenen F, Leng P (2002) Finding association rules with some very frequent
attributes. In: Elomaa T, Mannila H, Toivonen H (eds): Principles of Data Min-
ing and Knowledge Discovery - Proceedings of the 6th European Conference
on Principles and Practice of Knowledge Discovery in Databases (PKDD-02,
Springer, Berlin Heidelberg New York), Helsinki, Finland, August 2002. (LNAI
2431, ISBN 3-540-44037-2, pages 99-111)
14. Coenen F (2003) The LUCS-KDD discretised/normalised ARM and CARM
data library. http://www.csc.liv.ac.uk/ frans/KDD/Software/LUCS-KDD-
DN/, Department of Computer Science, The University of Liverpool, UK
15. Coenen F, Leng P (2004) An evaluation of approaches to classification rule
selection. In: Proceedings of the Fourth IEEE International Conference on Data
Mining (ICDM-04, IEEE Computer Society), Brighton, UK, November 2004.
(ISBN 0-7695-2142-8, pages 359-362)
16. Coenen F, Leng P, Ahmed S (2004) Data structure for association rule mining:
T-trees and p-trees. IEEE Transactions on Knowledge and Data Engineering,
Volume 16(6):774-778
17. Coenen F, Leng P, Goulbourne G (2004) Tree structures for mining association
rules. Journal of Data Mining and Knowledge Discovery, Volume 8(1):25-51
18. Coenen F, Leng P, Zhang L (2005) Threshold tuning for improved classifica-
tion association rule mining. In: Ho TB, Cheung D, Liu H (eds): Advances in
Knowledge Discovery and Data Mining - Proceedings of the Ninth Pacific-Asia
Conference on Knowledge Discovery and Data Mining (PAKDD-05, Springer,
Berlin Heidelberg New York), Hanoi, Vietnam, May 2005. (LNAI 3518, ISBN
3-540-26076-5, pages 216-225)
19. De Bonis A, Gasieniec L, Vaccaro U (2003) Generalized framework for se-
lectors with applications in optimal group testing. In: Baeten JCM, Lenstra
JK, Parrow J, Woeginger GJ (eds): Proceedings of the Thirtieth International
Colloquium on Automata, Languages and Programming (ICALP-03, Springer,
Berlin Heidelberg New York), Eindhoven, The Netherlands, June 30-July 4,
2003. (LNAI 2719, ISBN 3-540-40493-7, pages 81-96)
20. Domingos P, Pazzani M (1997) On the optimality of the simple bayesian clas-
sifier under zero-one loss. Machine Learning, 29(2/3):103-130.
21. Dong G, Li J (1999) E
cient mining of emerging patterns: Discovering trends
and differences. In: Proceedings of the Fifth ACM SIGKDD International Con-
ference on Knowledge Discovery and Data Mining (KDD-99, ACM, New York,
NY), San Diego, CA, United States, August 1999. (pages 43-52)
22. Dong G, Zhang X, Wong L, Li J (1999) CAEP: Classification by aggregat-
ing emerging patterns. In: Arikawa S, Furukawa K (eds): Discovery Science -
