-
1
-
-
0027621699
-
Mining associations between sets of items in massive databases
-
Washington, DC, May
-
Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining associations between sets of items in massive databases. In Proceedings of the 1993 ACM-SIGMOD international conference on management of data (pp. 207-216). Washington, DC, May 1993.
-
(1993)
Proceedings of the 1993 ACM-SIGMOD International Conference on Management of Data
, pp. 207-216
-
-
Agrawal, R.1
Imielinski, T.2
Swami, A.3
-
3
-
-
84867817851
-
Mining minimal non-redundant association rules using frequent closed itemsets
-
Springer Berlin
-
Bastide, Y., Pasquier, N., Taouil, R., Stumme, G., & Lakhal, L. (2000). Mining minimal non-redundant association rules using frequent closed itemsets. In First international conference on computational logic-CL 2000 (pp. 972-986). Berlin: Springer.
-
(2000)
First International Conference on Computational Logic-CL 2000
, pp. 972-986
-
-
Bastide, Y.1
Pasquier, N.2
Taouil, R.3
Stumme, G.4
Lakhal, L.5
-
5
-
-
23044517681
-
Constraint-based rule mining in large, dense databases
-
2/3
-
Bayardo, R. J. Jr., Agrawal, R., & Gunopulos, D. (2000). Constraint-based rule mining in large, dense databases. Data Mining and Knowledge Discovery, 4(2/3), 217-240.
-
(2000)
Data Mining and Knowledge Discovery
, vol.4
, pp. 217-240
-
-
Bayardo Jr. R., J.1
Agrawal, R.2
Gunopulos, D.3
-
6
-
-
0001677717
-
Controlling the false discovery rate: A new and powerful approach to multiple testing
-
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A new and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B, 57, 289-300.
-
(1995)
Journal of the Royal Statistical Society Series B
, vol.57
, pp. 289-300
-
-
Benjamini, Y.1
Hochberg, Y.2
-
7
-
-
0013110524
-
Using association rules for product assortment decisions: A case study
-
ACM New York
-
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (1999). Using association rules for product assortment decisions: A case study. In Proceedings of the fifth ACM SIGKDD international conference on knowledge discovery and data mining (pp. 254-260). New York: ACM.
-
(1999)
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 254-260
-
-
Brijs, T.1
Swinnen, G.2
Vanhoof, K.3
Wets, G.4
-
8
-
-
0031161999
-
Beyond market baskets: Generalizing association rules to correlations
-
ACM New York
-
Brin, S., Motwani, R., & Silverstein, C. (1997). Beyond market baskets: Generalizing association rules to correlations. In J. Peckham (Ed.), SIGMOD 1997, Proceedings ACM SIGMOD international conference on management of data, May 1997 (pp. 265-276). New York: ACM.
-
(1997)
SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data May 1997
, pp. 265-276
-
-
Brin, S.1
Motwani, R.2
Silverstein, C.3
Peckham, J.4
-
11
-
-
33749583834
-
Assessing data mining results via swap randomization
-
Gionis, A., Mannila, H., Mielikainen, T., & Tsaparas, P. (2006). Assessing data mining results via swap randomization. In 12th international conference on knowledge discovery and data mining (KDD) (pp. 167-176).
-
(2006)
12th International Conference on Knowledge Discovery and Data Mining (KDD)
, pp. 167-176
-
-
Gionis, A.1
Mannila, H.2
Mielikainen, T.3
Tsaparas, P.4
-
12
-
-
78149328321
-
Mining top-K frequent closed patterns without minimum support
-
Han, J., Wang, J., Lu, Y., & Tzvetkov, P. (2002). Mining top-K frequent closed patterns without minimum support. In International conference on data mining (pp. 211-218).
-
(2002)
International Conference on Data Mining
, pp. 211-218
-
-
Han, J.1
Wang, J.2
Lu, Y.3
Tzvetkov, P.4
-
13
-
-
0003704318
-
-
Department of Information and Computer Science, University of California, Irvine, CA
-
Hettich, S., & Bay, S. D. (2007). The UCI KDD archive. Department of Information and Computer Science, University of California, Irvine, CA. http://kdd.ics.uci.edu.
-
(2007)
The UCI KDD Archive
-
-
Hettich, S.1
Bay, S.D.2
-
14
-
-
0000244636
-
Improved Bonferroni-type multiple testing procedures
-
1
-
Holland, B. S., & Copenhaver, M. D. (1988). Improved Bonferroni-type multiple testing procedures. Psychological Bulletin, 104(1), 145-149.
-
(1988)
Psychological Bulletin
, vol.104
, pp. 145-149
-
-
Holland, B.S.1
Copenhaver, M.D.2
-
15
-
-
0002294347
-
A simple sequentially rejective multiple test procedure
-
Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 65-70.
-
(1979)
Scandinavian Journal of Statistics
, vol.6
, pp. 65-70
-
-
Holm, S.1
-
17
-
-
12244313033
-
Interestingness of frequent itemsets using Bayesian networks as background knowledge
-
ACM New York
-
Jaroszewicz, S., & Simovici, D. A. (2004). Interestingness of frequent itemsets using Bayesian networks as background knowledge. In R. Kohavi, J. Gehrke, & J. Ghosh (Eds.), KDD-2004: Proceedings of the tenth ACM SIGKDD international conference on knowledge discovery and data mining, August 2004 (pp. 178-186). New York: ACM.
-
(2004)
KDD-2004: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining August 2004
, pp. 178-186
-
-
Jaroszewicz, S.1
Simovici, D.A.2
Kohavi, R.3
Gehrke, J.4
Ghosh, J.5
-
18
-
-
0002192370
-
Explora: A multipattern and multistrategy discovery assistant
-
AAAI Menlo Park
-
Klösgen, W. (1996). Explora: A multipattern and multistrategy discovery assistant. In U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, & R. Uthurusamy (Eds.), Advances in knowledge discovery and data mining (pp. 249-271). Menlo Park: AAAI.
-
(1996)
Advances in Knowledge Discovery and Data Mining
, pp. 249-271
-
-
Klösgen, W.1
Fayyad, U.2
Piatetsky-Shapiro, G.3
Smyth, P.4
Uthurusamy, R.5
-
19
-
-
0001267179
-
Pruning and summarizing the discovered associations
-
AAAI New York
-
Liu, B., Hsu, W., & Ma, Y. (1999). Pruning and summarizing the discovered associations. In Proceedings of the fifth ACM SIGKDD international conference on knowledge discovery and data mining (KDD-99), August 1999 (pp. 125-134). New York: AAAI.
-
(1999)
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-99) August 1999
, pp. 125-134
-
-
Liu, B.1
Hsu, W.2
Ma, Y.3
-
21
-
-
33750337560
-
Why is rule learning optimistic and how to correct it
-
Springer Berlin
-
Možina, M., Demšar, J., Žabkar, J., & Bratko, I. (2006). Why is rule learning optimistic and how to correct it. In Machine learning: ECML 2006 (pp. 330-340). Berlin: Springer.
-
(2006)
Machine Learning: ECML 2006
, pp. 330-340
-
-
Možina, M.1
Demšar, J.2
Žabkar, J.3
Bratko, I.4
-
22
-
-
33745834241
-
-
Department of Information and Computer Science, University of California, Irvine, CA
-
Newman, D. J., Hettich, S., Blake, C., & Merz, C. J. (2007). UCI repository of machine learning databases (Machine-readable data repository). Department of Information and Computer Science, University of California, Irvine, CA.
-
(2007)
UCI Repository of Machine Learning Databases (Machine-readable Data Repository)
-
-
Newman, D.J.1
Hettich, S.2
Blake, C.3
Merz, C.J.4
-
23
-
-
0002877253
-
Discovery, analysis, and presentation of strong rules
-
AAAI/MIT Press Menlo Park
-
Piatetsky-Shapiro, G. (1991). Discovery, analysis, and presentation of strong rules. In G. Piatetsky-Shapiro & J. Frawley (Eds.), Knowledge discovery in databases (pp. 229-248). Menlo Park: AAAI/MIT Press.
-
(1991)
Knowledge Discovery in Databases
, pp. 229-248
-
-
Piatetsky-Shapiro, G.1
Piatetsky-Shapiro, G.2
Frawley, J.3
-
24
-
-
33749539847
-
Finding association rules that trade support optimally against confidence
-
4
-
Scheffer, T. (1995). Finding association rules that trade support optimally against confidence. Intelligent Data Analysis, 9(4), 381-395.
-
(1995)
Intelligent Data Analysis
, vol.9
, pp. 381-395
-
-
Scheffer, T.1
-
25
-
-
0141719772
-
Finding the most interesting patterns in a database quickly by using sequential sampling
-
Scheffer, T., & Wrobel, S. (2002). Finding the most interesting patterns in a database quickly by using sequential sampling. Journal of Machine Learning Research, 3, 833-862.
-
(2002)
Journal of Machine Learning Research
, vol.3
, pp. 833-862
-
-
Scheffer, T.1
Wrobel, S.2
-
26
-
-
0000835392
-
OPUS: An efficient admissible algorithm for unordered search
-
Webb, G. I. (1995). OPUS: An efficient admissible algorithm for unordered search. Journal of Artificial Intelligence Research, 3, 431-465.
-
(1995)
Journal of Artificial Intelligence Research
, vol.3
, pp. 431-465
-
-
Webb, G.I.1
-
29
-
-
33749562096
-
Discovering significant rules
-
ACM New York
-
Webb, G. I. (2006). Discovering significant rules. In L. Ungar, M. Craven, D. Gunopulos, & T. Eliassi-Rad (Eds.), Proceedings of the twelfth ACM SIGKDD international conference on knowledge discovery and data mining, KDD-2006 (pp. 434-443). New York: ACM.
-
(2006)
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD-2006
, pp. 434-443
-
-
Webb, G.I.1
Ungar, L.2
Craven, M.3
Gunopulos, D.4
Eliassi-Rad, T.5
-
30
-
-
34249653461
-
Discovering significant patterns
-
1
-
Webb, G. I. (2007). Discovering significant patterns. Machine Learning, 68(1), 1-33.
-
(2007)
Machine Learning
, vol.68
, pp. 1-33
-
-
Webb, G.I.1
-
32
-
-
4444337294
-
Mining non-redundant association rules
-
3
-
Zaki, M. J. (2004). Mining non-redundant association rules. Data Mining and Knowledge Discovery, 9(3), 223-248.
-
(2004)
Data Mining and Knowledge Discovery
, vol.9
, pp. 223-248
-
-
Zaki, M.J.1
-
33
-
-
12244294068
-
On the discovery of significant statistical quantitative rules
-
ACM New York
-
Zhang, H., Padmanabhan, B., & Tuzhilin, A. (2004). On the discovery of significant statistical quantitative rules. In Proceedings of the tenth international conference on knowledge discovery and data mining (KDD-2004), August 2004 (pp. 374-383). New York: ACM.
-
(2004)
Proceedings of the Tenth International Conference on Knowledge Discovery and Data Mining (KDD-2004) August 2004
, pp. 374-383
-
-
Zhang, H.1
Padmanabhan, B.2
Tuzhilin, A.3
-
34
-
-
0035788918
-
Real world performance of association rule algorithms
-
ACM New York
-
Zheng, Z., Kohavi, R., & Mason, L. (2001). Real world performance of association rule algorithms. In Proceedings of the seventh international conference on knowledge discovery and data mining (KDD-2001), August 2001 (pp. 401-406). New York: ACM.
-
(2001)
Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining (KDD-2001) August 2001
, pp. 401-406
-
-
Zheng, Z.1
Kohavi, R.2
Mason, L.3
|