-
1
-
-
0027621699
-
Mining association rules between sets of items in large databases
-
Washington, D.C., May 1993
-
Agrawal, R., Imielinski, T., & Swami, T. (1993). Mining association rules between sets of items in large databases. In Proceedings of the ACM Int. Conf. on Management of Data, Washington, D.C., May 1993 (pp. 207-216).
-
(1993)
In Proceedings of the ACM Int. Conf. on Management of Data
, pp. 207-216
-
-
Agrawal, R.1
Imielinski, T.2
Swami, T.3
-
2
-
-
34248650696
-
Redundant association rules reduction techniques
-
Ashrafi, M. Z., Taniar, D., & Smith, K. (2007). Redundant association rules reduction techniques. International Journal of Business Intelligence and Data Mining, 2(1), 29-63.
-
(2007)
International Journal of Business Intelligence and Data Mining
, vol.2
, Issue.1
, pp. 29-63
-
-
Ashrafi, M.Z.1
Taniar, D.2
Smith, K.3
-
3
-
-
22944455028
-
Post-processing of association rules
-
Boston, Massachusetts, 20-23 Aug 2000
-
Baesens, B., Viaene, S., & Vanthienen, J. (2000). Post-processing of association rules. In Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'2000), Boston, Massachusetts, 20-23 Aug 2000 (pp. 2-8).
-
(2000)
In Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'2000)
, pp. 2-8
-
-
Baesens, B.1
Viaene, S.2
Vanthienen, J.3
-
4
-
-
11344271623
-
Essential classification rule sets
-
Baralis, E., & Chiusano, S. (2004). Essential Classification Rule Sets. ACM Transactions on Database Systems, 29(4), 635-674.
-
(2004)
ACM Transactions on Database Systems
, vol.29
, Issue.4
, pp. 635-674
-
-
Baralis, E.1
Chiusano, S.2
-
5
-
-
0031191449
-
Designing templates for mining association rules
-
Baralis, E., & Psaila, G. (1997). Designing templates for mining association rules, Journal of Intelligent Information Systems, 9(1), 7-32.
-
(1997)
Journal of Intelligent Information Systems
, vol.9
, Issue.1
, pp. 7-32
-
-
Baralis, E.1
Psaila, G.2
-
6
-
-
77957911195
-
-
Institute of Information and Computing Sciences, Technical reports, UU-CS-2006-048, Utrecht University
-
Bathoorn, R., Koopman, A., & Siebes, A. (2006). Frequent Patterns that Compress. Institute of Information and Computing Sciences, Technical reports, UU-CS-2006-048, Utrecht University.
-
(2006)
Frequent Patterns that Compress
-
-
Bathoorn, R.1
Koopman, A.2
Siebes, A.3
-
8
-
-
34147208482
-
Using metarules to organize and group discovered association rules
-
Berrado, A., & Runger, G.C. (2007). Using metarules to organize and group discovered association rules. Data Mining and Knowledge Discovery, 14(3), 409-431.
-
(2007)
Data Mining and Knowledge Discovery
, vol.14
, Issue.3
, pp. 409-431
-
-
Berrado, A.1
Runger, G.C.2
-
9
-
-
33845966417
-
Guest editors' introduction
-
Berzal, F., & Cubero, J.C. (2007). Guest editors' introduction, Data & Knowledge Engineering, Special section on Intelligent Data Mining, 60, 1-4.
-
(2007)
Data & Knowledge Engineering, Special Section on Intelligent Data Mining
, vol.60
, pp. 1-4
-
-
Berzal, F.1
Cubero, J.C.2
-
10
-
-
0003408496
-
-
Department of Information and Computer Science, University of California, Irvine
-
Blake, L. C., & Merz, J. C. (1998). UCI Repository of Machine Learning Databases. Department of Information and Computer Science, University of California, Irvine, http://www.ics.uci.edu/~mlearn/MLRepository.html.
-
(1998)
UCI Repository of Machine Learning Databases
-
-
Blake, L.C.1
Merz, J.C.2
-
11
-
-
0012903635
-
-
Available from
-
Borgelt, C. (2000). Apriori software. Available from http://www.borgelt.net/software.html.
-
(2000)
Apriori Software
-
-
Borgelt, C.1
-
12
-
-
0037243046
-
Free-sets: A condensed representation of boolean data for the approximation of frequency queries
-
Boulicaut, J. F., Bykowski, A., & Rigotti, C. (2003). Free-sets: a condensed representation of boolean data for the approximation of frequency queries. Data Mining and Knowledge Discovery, 7(1), 5-22.
-
(2003)
Data Mining and Knowledge Discovery
, vol.7
, Issue.1
, pp. 5-22
-
-
Boulicaut, J.F.1
Bykowski, A.2
Rigotti, C.3
-
13
-
-
22944451216
-
Reducing redundancy in characteristic rule discovery by using integer programming techniques
-
Brijs, T., Vanhoof, K., & Wets, G. (2000). Reducing Redundancy in Characteristic Rule Discovery By Using Integer Programming Techniques. Intelligent Data Analysis Journal, 4(3), 229-240.
-
(2000)
Intelligent Data Analysis Journal
, vol.4
, Issue.3
, pp. 229-240
-
-
Brijs, T.1
Vanhoof, K.2
Wets, G.3
-
14
-
-
11344285341
-
Beyond market baskets: Generalizing association rules to dependence rules
-
Brin, S., Motwani, R., & Silverstein, C. (1998). Beyond market baskets: Generalizing association rules to dependence rules. Data Mining and Knowledge Discovery, 2(1), 39-68.
-
(1998)
Data Mining and Knowledge Discovery
, vol.2
, Issue.1
, pp. 39-68
-
-
Brin, S.1
Motwani, R.2
Silverstein, C.3
-
15
-
-
0031162961
-
Dynamic itemset counting and implication rules for market basket data
-
May 13-15, Tucson, Arizona, USA, 1997
-
Brin, S., Motwani, R., Ullman, J. D., & Tsur, S. (1997). Dynamic itemset counting and implication rules for market basket data. In Proceedings of the ACM SIGMOD Conference on Management of Data, May 13-15, Tucson, Arizona, USA, 1997 (pp. 255-264).
-
(1997)
In Proceedings of the ACM SIGMOD Conference on Management of Data
, pp. 255-264
-
-
Brin, S.1
Motwani, R.2
Ullman, J.D.3
Tsur, S.4
-
16
-
-
36749073857
-
From machine learning to knowledge discovery: Survey of preprocessing and postprocessing
-
Bruha, I. (2000). From machine learning to knowledge discovery: Survey of preprocessing and postprocessing. Intelligent Data Analysis, 4(3-4), 363-374.
-
(2000)
Intelligent Data Analysis
, vol.4
, Issue.3-4
, pp. 363-374
-
-
Bruha, I.1
-
18
-
-
33745145777
-
A survey on condensed representations for frequent sets
-
In: J.F. Boulicaut, L.D. Raedt, & H. Mannila (Ed.), Springer
-
Calders, T., Rigotti, C., & Boulicaut, J. F. (2006). A Survey on Condensed Representations for Frequent Sets, In: J.F. Boulicaut, L.D. Raedt, & H. Mannila (Ed.), Constraint-based mining and Inductive Databases (pp. 64-80), Springer.
-
(2006)
Constraint-based Mining and Inductive Databases
, pp. 64-80
-
-
Calders, T.1
Rigotti, C.2
Boulicaut, J.F.3
-
21
-
-
38749135862
-
Effective elimination of redundant association rules
-
Cheng, J., Ke, Y., & Ng, W. (2008). Effective elimination of redundant association rules, Data Mining and Knowledge Discovery, 16, 221-249.
-
(2008)
Data Mining and Knowledge Discovery
, vol.16
, pp. 221-249
-
-
Cheng, J.1
Ke, Y.2
Ng, W.3
-
23
-
-
0002283033
-
From data mining to knowledge discovery in databases
-
Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17, 37-54.
-
(1996)
AI Magazine
, vol.17
, pp. 37-54
-
-
Fayyad, U.1
Piatetsky-Shapiro, G.2
Smyth, P.3
-
24
-
-
33745947342
-
Minimal decision rules based on the apriori algorithm
-
Fernádez, M. Z., Menasalvas, E., Marbán, O., Peña, J. M., & Millán S. (2001). Minimal Decision Rules Based on the Apriori Algorithm, Internal Journal of Applied Mathematics and Computer Science, 11(3), 691-704.
-
(2001)
Internal Journal of Applied Mathematics and Computer Science
, vol.11
, Issue.3
, pp. 691-704
-
-
Fernádez, M.Z.1
Menasalvas, E.2
Marbán, O.3
Peña, J.M.4
Millán, S.5
-
25
-
-
84900260936
-
-
FIMI Dataset Repository, Available from
-
FIMI Dataset Repository. (2003). Available from http://fimi.cs.helsinki.fi/data/.
-
(2003)
-
-
-
26
-
-
33749319347
-
Interestingness measures for data mining: A survey
-
No.9
-
Geng, L., & Hamilton, H. J. (2006). Interestingness Measures for Data Mining: A Survey. ACM Computing Surveys, 38(3), No.9.
-
(2006)
ACM Computing Surveys
, vol.38
, Issue.3
-
-
Geng, L.1
Hamilton, H.J.2
-
27
-
-
77953895092
-
Efficient management of non redundant rules in large pattern bases: A bitmap approach
-
In, 2006
-
Jacquenet, F., Largeron, C., & Udrea, C. (2006). Efficient Management of Non Redundant Rules in Large Pattern Bases: A Bitmap Approach. In Proceedings of the International Conference on Enterprise Information Systems, 2006 (pp. 208-215).
-
(2006)
Proceedings of the International Conference on Enterprise Information Systems
, pp. 208-215
-
-
Jacquenet, F.1
Largeron, C.2
Udrea, C.3
-
29
-
-
0003113325
-
Finding interesting rules from large sets of discovered association rules
-
Gaithersburg, Maryland, USA
-
Klemettinen, M., Mannila, H., Ronkainen, P., Toivonen, H., & Verkamo, A.I. (1994). Finding interesting rules from large sets of discovered association rules. In Proceedings of the Third International Conference on Information and Knowledge Management (CIKM'94), Gaithersburg, Maryland, USA (pp. 401-408).
-
(1994)
In Proceedings of the Third International Conference on Information and Knowledge Management (CIKM'94)
, pp. 401-408
-
-
Klemettinen, M.1
Mannila, H.2
Ronkainen, P.3
Toivonen, H.4
Verkamo, A.I.5
-
33
-
-
78149313084
-
Cmar: Accurate and efficient classification based on multiple class-association rules
-
2001
-
Li, W., Han, J., & Pei, J. (2001). CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules, In Proceedings of the 2001 IEEE International Conference on Data Mining, 2001 (pp. 369-376).
-
(2001)
In Proceedings of the 2001 IEEE International Conference on Data Mining
, pp. 369-376
-
-
Li, W.1
Han, J.2
Pei, J.3
-
35
-
-
0001267179
-
Pruning and summarizing the discovered association
-
1999, Philadelphia, Penn
-
Liu, B., Hsu, W., & Ma, Y. (1999). Pruning and summarizing the discovered association. In Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999, Philadelphia, Penn (pp. 125-134).
-
(1999)
In Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 125-134
-
-
Liu, B.1
Hsu, W.2
Ma, Y.3
-
36
-
-
33847113992
-
Association rules mining using heavy itemsets
-
Palshikar, G. K., Kale, M. S., & Apte, M. M. (2007). Association rules mining using heavy itemsets. Data & Knowledge Engineering, 61(1), 93-113.
-
(2007)
Data & Knowledge Engineering
, vol.61
, Issue.1
, pp. 93-113
-
-
Palshikar, G.K.1
Kale, M.S.2
Apte, M.M.3
-
37
-
-
17444386019
-
Generating a condensed representation for association rules
-
Pasquier, N., Taouil, R., Bastide, Y., Stumme, G., & Lakhal, L. (2005). Generating a Condensed Representation for Association Rules. Journal of Intelligent Information Systems, 24(1), 29-60.
-
(2005)
Journal of Intelligent Information Systems
, vol.24
, Issue.1
, pp. 29-60
-
-
Pasquier, N.1
Taouil, R.2
Bastide, Y.3
Stumme, G.4
Lakhal, L.5
-
38
-
-
0002880407
-
-
1995
-
Srikant, R., & Agrawal, R. (1995). Mining Generalized Association Rules. In Proceedings of the 1995 Int. Conf. Very Large Data Bases, Zurich, Switzerland, 1995 (pp. 407-419).
-
(1995)
In Proceedings of the 1995 Int. Conf. Very Large Data Bases, Zurich, Switzerland
, pp. 407-419
-
-
Srikant, R.1
Agrawal, R.2
-
39
-
-
0002592397
-
Pruning and grouping of discovered association rules
-
Heraklion, Crete, Greece, 1995
-
Toivonen, H., Klemettinen, M., Ronkainen, P., Hätönen, K., & Mannila, H. (1995). Pruning and Grouping of Discovered Association Rules. In Proceedings of ECML-95 Workshop on Statistics, Machine Learning, and Discovery in Databases, Heraklion, Crete, Greece, 1995 (pp. 47-52).
-
(1995)
In Proceedings of ECML-95 Workshop on Statistics, Machine Learning, and Discovery in Databases
, pp. 47-52
-
-
Toivonen, H.1
Klemettinen, M.2
Ronkainen, P.3
Hätönen, K.4
Mannila, H.5
-
40
-
-
34247475039
-
Lcm: An efficient algorithm for enumerating frequent closed item sets
-
Uno, T., Asai, T., Arimura, H. & Uchida, Y. (2003). LCM: An Efficient Algorithm for Enumerating Frequent Closed Item Sets. In Proceedings of ICDM'03 Workshop on Frequent Itemset Mining Implementations (pp. 1-10).
-
(2003)
In Proceedings of ICDM'03 Workshop on Frequent Itemset Mining Implementations
, pp. 1-10
-
-
Uno, T.1
Asai, T.2
Arimura, H.3
Uchida, Y.4
-
41
-
-
33747879040
-
Bootstrapping rule induction to achieve rule stability and reduction
-
Waitman, L. R., Fisher, D. H., & King P. H. (2006). Bootstrapping rule induction to achieve rule stability and reduction. Journal of Intelligent Information System, 27, 49-77.
-
(2006)
Journal of Intelligent Information System
, vol.27
, pp. 49-77
-
-
Waitman, L.R.1
Fisher, D.H.2
King, P.H.3
-
42
-
-
14844340628
-
K-optimal rule discovery
-
Webb, G. I., & Zhang, S. (2005). K-Optimal Rule Discovery. Data Mining and Knowledge Discovery, 10(1), 39-79.
-
(2005)
Data Mining and Knowledge Discovery
, vol.10
, Issue.1
, pp. 39-79
-
-
Webb, G.I.1
Zhang, S.2
-
43
-
-
4444337294
-
Mining non-redundant association rules
-
Zaki, M. J. (2004). Mining Non-Redundant Association Rules. Data Mining and Knowledge Discovery, 9, 223-248.
-
(2004)
Data Mining and Knowledge Discovery
, vol.9
, pp. 223-248
-
-
Zaki, M.J.1
|