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Volumn 13, Issue 2, 2006, Pages 167-192

A systematic approach to the assessment of fuzzy association rules

Author keywords

Association rules; Fuzzy partition; Fuzzy sets; Quality measures

Indexed keywords

DATA MINING; KNOWLEDGE BASED SYSTEMS; PROBLEM SOLVING; SEMANTICS; SET THEORY;

EID: 33748458842     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-005-0032-4     Document Type: Article
Times cited : (165)

References (99)
  • 3
    • 0013421491 scopus 로고
    • On a family of connectives for fuzzy sets
    • Alsina C (1985) On a family of connectives for fuzzy sets. Fuzzy Sets Syst 16:231-235
    • (1985) Fuzzy Sets Syst , vol.16 , pp. 231-235
    • Alsina, C.1
  • 4
    • 0020735917 scopus 로고
    • On some logical connective for fuzzy sets theory
    • Alsina C, Trillas E, Valverde L (1983) On some logical connective for fuzzy sets theory. J Math Anal Appl 93:15-26
    • (1983) J Math Anal Appl , vol.93 , pp. 15-26
    • Alsina, C.1    Trillas, E.2    Valverde, L.3
  • 6
    • 0033281173 scopus 로고    scopus 로고
    • FARM: A data mining system for discovering fuzzy association rules
    • Seoul, Korea
    • Au W-H, Chan KCC (1999) FARM: A data mining system for discovering fuzzy association rules. In: Proceedings of the FUZZ-IEEE-99. Seoul, Korea, pp 1217-1222
    • (1999) Proceedings of the FUZZ-IEEE-99 , pp. 1217-1222
    • Au, W.-H.1    Chan, K.C.C.2
  • 7
    • 0037390557 scopus 로고    scopus 로고
    • Mining fuzzy association rules in a bank-account database
    • Au W-H, Chan KCC (2003) Mining fuzzy association rules in a bank-account database. IEEE Trans Fuzzy Syst 11(2):238-248
    • (2003) IEEE Trans Fuzzy Syst , vol.11 , Issue.2 , pp. 238-248
    • Au, W.-H.1    Chan, K.C.C.2
  • 8
    • 9644300959 scopus 로고    scopus 로고
    • Mining changes in association rules: A fuzzy approach
    • Au W-H, Chan KCC (2005) Mining changes in association rules: A fuzzy approach. Fuzzy Sets Syst 149(1):87-104
    • (2005) Fuzzy Sets Syst , vol.149 , Issue.1 , pp. 87-104
    • Au, W.-H.1    Chan, K.C.C.2
  • 9
    • 0037282574 scopus 로고    scopus 로고
    • Extracting share frequent itemsets with infrequent subsets
    • Barber B, Hamilton HJ (2003) Extracting share frequent itemsets with infrequent subsets. Data Min Knowl Disc 7:153-185
    • (2003) Data Min Knowl Disc , vol.7 , pp. 153-185
    • Barber, B.1    Hamilton, H.J.2
  • 10
    • 0040038386 scopus 로고    scopus 로고
    • Fuzzy Galois connections
    • Belohlavek R (1999) Fuzzy Galois connections. Math Logic J 45(4):497-504
    • (1999) Math Logic J , vol.45 , Issue.4 , pp. 497-504
    • Belohlavek, R.1
  • 12
    • 0035792442 scopus 로고    scopus 로고
    • On some fuzzy extensions of association rules
    • Vancouver, Canada
    • Bosc P, Pivert O (2001) On some fuzzy extensions of association rules. In: Proc. IFSA/NAFIPS-2001. Vancouver, Canada
    • (2001) Proc. IFSA/NAFIPS-2001
    • Bosc, P.1    Pivert, O.2
  • 14
    • 0036850692 scopus 로고    scopus 로고
    • Fuzzy association rules and the extended mining algorithms
    • Chen G, Wei Q (2002) Fuzzy association rules and the extended mining algorithms. M Sci 147(1-4):201-228
    • (2002) M Sci , vol.147 , Issue.1-4 , pp. 201-228
    • Chen, G.1    Wei, Q.2
  • 16
    • 0002682767 scopus 로고    scopus 로고
    • Fuzzy data mining: Discovery of fuzzy generalized association rules
    • Bordogna G, Pasi G (eds). Springer-Verlag
    • Chen G, Wei Q, Kerre EE (2000) Fuzzy data mining: Discovery of fuzzy generalized association rules. In: Bordogna G, Pasi G (eds) Recent issues on fuzzy databases. Springer-Verlag
    • (2000) Recent Issues on Fuzzy Databases
    • Chen, G.1    Wei, Q.2    Kerre, E.E.3
  • 19
    • 3042687748 scopus 로고    scopus 로고
    • Data structures for association rule mining: T-trees and P-trees
    • Coenen F, Leng P, Ahmed S (2004b) Data structures for association rule mining: T-trees and P-trees. IEEE Trans Knowl Data Eng 16(6):774-778
    • (2004) IEEE Trans Knowl Data Eng , vol.16 , Issue.6 , pp. 774-778
    • Coenen, F.1    Leng, P.2    Ahmed, S.3
  • 22
  • 23
    • 6344254129 scopus 로고    scopus 로고
    • Acquisition of fuzzy association rules from medical data
    • Barro S, Marin R (eds). Physica Verlag
    • Delgado M, Sanchez D, Vila MA (2000) Acquisition of fuzzy association rules from medical data. In: Barro S, Marin R (eds) Fuzzy logic in medicine. Physica Verlag
    • (2000) Fuzzy Logic in Medicine
    • Delgado, M.1    Sanchez, D.2    Vila, M.A.3
  • 25
    • 7044250743 scopus 로고    scopus 로고
    • A note on quality measures for fuzzy association rules
    • Proceedings of the IFSA-03, 10th international fuzzy systems association world congress. Springer-Verlag, Istambul
    • Dubois D, Hüllermeier E, Prade H (2003) A note on quality measures for fuzzy association rules. In: Proceedings of the IFSA-03, 10th international fuzzy systems association world congress, number 2715 in LNAI. Springer-Verlag, Istambul, pp 677-648
    • (2003) LNAI , vol.2715 , pp. 677-1648
    • Dubois, D.1    Hüllermeier, E.2    Prade, H.3
  • 26
  • 27
    • 0001000564 scopus 로고
    • Fuzzy cardinality and the modeling of imprecise quantification
    • Dubois D, Prade H (1985) Fuzzy cardinality and the modeling of imprecise quantification. Fuzzy Sets Syst 16:199-230
    • (1985) Fuzzy Sets Syst , vol.16 , pp. 199-230
    • Dubois, D.1    Prade, H.2
  • 28
    • 0001152901 scopus 로고
    • Gradual inference rules in approximate reasoning
    • Dubois D, Prade H (1992) Gradual inference rules in approximate reasoning. Inf Sci 61(1,2):103-122
    • (1992) Inf Sci , vol.61 , Issue.1-2 , pp. 103-122
    • Dubois, D.1    Prade, H.2
  • 29
    • 0028698846 scopus 로고
    • Conditional objects as non-monotonic consequence relationships
    • Dubois D, Prade H (1994) Conditional objects as non-monotonic consequence relationships. IEEE Trans Syst Man Cybern 24(12):1724-1739
    • (1994) IEEE Trans Syst Man Cybern , vol.24 , Issue.12 , pp. 1724-1739
    • Dubois, D.1    Prade, H.2
  • 30
    • 0030577310 scopus 로고    scopus 로고
    • What are fuzzy rules and how to use them
    • Dubois D, Prade H (1996) What are fuzzy rules and how to use them. Fuzzy Sets Syst 84:169-185
    • (1996) Fuzzy Sets Syst , vol.84 , pp. 169-185
    • Dubois, D.1    Prade, H.2
  • 33
    • 17744368529 scopus 로고    scopus 로고
    • On the representation, measurement, and discovery of fuzzy associations
    • Dubois D, Prade H, Sudkamp T (2005) On the representation, measurement, and discovery of fuzzy associations. IEEE Trans on Fuzzy Syst 13(2):250-262
    • (2005) IEEE Trans on Fuzzy Syst , vol.13 , Issue.2 , pp. 250-262
    • Dubois, D.1    Prade, H.2    Sudkamp, T.3
  • 35
    • 0001070713 scopus 로고
    • On the simultaneous associativity of f(x, y) and x + y - F(x, y)
    • Frank MJ (1979) On the simultaneous associativity of f(x, y) and x + y - f(x, y). Aeq Math 19:194-226
    • (1979) Aeq Math , vol.19 , pp. 194-226
    • Frank, M.J.1
  • 37
    • 0013460037 scopus 로고
    • Meta-rule-guidedmining of association rules in relational databases
    • Singapore
    • Fu Y, Han J (1995) Meta-rule-guidedmining of association rules in relational databases. In: KDOOD/TDOOD. Singapore, pp 39-46
    • (1995) KDOOD/TDOOD , pp. 39-46
    • Fu, Y.1    Han, J.2
  • 39
    • 27544478009 scopus 로고    scopus 로고
    • Advances in frequent itemset mining implementations: Report on FIMI'03
    • Goethals B, Zaki MJ (2004) Advances in frequent itemset mining implementations: Report on FIMI'03. SIGKDD Explorations 6(1):109-117
    • (2004) SIGKDD Explorations , vol.6 , Issue.1 , pp. 109-117
    • Goethals, B.1    Zaki, M.J.2
  • 41
    • 0003734239 scopus 로고    scopus 로고
    • A fuzzy approach for mining quantitative association rules
    • Turku Centre for Computer Science
    • Gyenesei A (2000) A fuzzy approach for mining quantitative association rules. Technical Report 336, Turku Centre for Computer Science
    • (2000) Technical Report , vol.336
    • Gyenesei, A.1
  • 42
    • 0003707613 scopus 로고    scopus 로고
    • Mining weighted association rules for fuzzy quantitative items
    • Turku Centre for Computer Science
    • Gyenesei A (2000) Mining weighted association rules for fuzzy quantitative items. Technical Report 346, Turku Centre for Computer Science
    • (2000) Technical Report , vol.346
    • Gyenesei, A.1
  • 43
    • 0035198467 scopus 로고    scopus 로고
    • A fuzzy approach for mining quantitative association rules
    • Gyenesei A (2001) A fuzzy approach for mining quantitative association rules. Acta Cybern 15:305-320
    • (2001) Acta Cybern , vol.15 , pp. 305-320
    • Gyenesei, A.1
  • 47
    • 2442449952 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation
    • Han J, Pei J, Yin Y, Mao R (2004) Mining frequent patterns without candidate generation. Data Min Knowl Disc 8:53-87
    • (2004) Data Min Knowl Disc , vol.8 , pp. 53-87
    • Han, J.1    Pei, J.2    Yin, Y.3    Mao, R.4
  • 48
    • 33748443147 scopus 로고
    • Harper WL, Stalnaker R, Pearce G (eds), Dordrecht, The Netherlands
    • Harper WL, Stalnaker R, Pearce G (eds) (1981) IFS. D. Reidel, Dordrecht, The Netherlands
    • (1981) IFS. D. Reidel
  • 50
    • 84883745941 scopus 로고    scopus 로고
    • Fuzzy association rules: Semantic issues and quality measures
    • Proceedings of the international conference on computational intelligence - 7th fuzzy days. Springer-Verlag, Dortmund, Germany
    • Hüllermeier E (2001) Fuzzy association rules: Semantic issues and quality measures. In: Proceedings of the international conference on computational intelligence - 7th fuzzy days, number 2206 in LNCS. Springer-Verlag, Dortmund, Germany, pp 380-391
    • (2001) LNCS , vol.2206 , pp. 380-391
    • Hüllermeier, E.1
  • 54
    • 17644408058 scopus 로고    scopus 로고
    • Genetic algorithm based framework for mining fuzzy association rules
    • Kaya M, Alhajj R (2005) Genetic algorithm based framework for mining fuzzy association rules. Fuzzy Sets Syst 152(3):587-601
    • (2005) Fuzzy Sets Syst , vol.152 , Issue.3 , pp. 587-601
    • Kaya, M.1    Alhajj, R.2
  • 58
    • 0025462359 scopus 로고
    • Nonmonotonic reasoning, preferential models and cumulative logics
    • Kraus S, Lehmann D, Magidor M (1990) Nonmonotonic reasoning, preferential models and cumulative logics. Artif Intell 44:167-207
    • (1990) Artif Intell , vol.44 , pp. 167-207
    • Kraus, S.1    Lehmann, D.2    Magidor, M.3
  • 59
    • 0348132918 scopus 로고    scopus 로고
    • Mining fuzzy association rules in databases
    • Kuok CM, Fu A, Hon Wong M (1998) Mining fuzzy association rules in databases. SIGMOD Record 27:41-46
    • (1998) SIGMOD Record , vol.27 , pp. 41-46
    • Kuok, C.M.1    Fu, A.2    Hon Wong, M.3
  • 61
    • 0037990663 scopus 로고
    • Probabilities of conditionals and conditional probabilities
    • Lewis D (1973) Probabilities of conditionals and conditional probabilities. J Philos Logic 3
    • (1973) J Philos Logic , vol.3
    • Lewis, D.1
  • 62
    • 0000418525 scopus 로고
    • Representations of associative functions
    • Ling CH (1965) Representations of associative functions. Publ Math Debrecen 12:189-212
    • (1965) Publ Math Debrecen , vol.12 , pp. 189-212
    • Ling, C.H.1
  • 63
    • 0015340630 scopus 로고
    • A definition of non-probabilistic entropy in the setting of fuzzy sets theory
    • De Luca A, Termini S (1972) A definition of non-probabilistic entropy in the setting of fuzzy sets theory. Inf Control 24:301-312
    • (1972) Inf Control , vol.24 , pp. 301-312
    • De Luca, A.1    Termini, S.2
  • 65
    • 0034247240 scopus 로고    scopus 로고
    • Mining fuzzy association rules and fuzzy frequency episodes for intrusion detection
    • Luo J, Bridges S (2000) Mining fuzzy association rules and fuzzy frequency episodes for intrusion detection. Int J Intell Syst 15(8):687-703
    • (2000) Int J Intell Syst , vol.15 , Issue.8 , pp. 687-703
    • Luo, J.1    Bridges, S.2
  • 66
    • 0016451032 scopus 로고
    • An experiment in linguistic synthesis with a fuzzy logic controller
    • Mamdani E, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man-Mach Stud 7:1-13
    • (1975) Int J Man-Mach Stud , vol.7 , pp. 1-13
    • Mamdani, E.1    Assilian, S.2
  • 71
    • 84911977993 scopus 로고    scopus 로고
    • Discovering frequent closed itemsets for association rules
    • Proceedings of the 7th international conference on database theory. Springer
    • Pasquier N, Bastide Y, Taouil R, Lakhal L (1999) Discovering frequent closed itemsets for association rules. In: Proceedings of the 7th international conference on database theory, number 1540 in LNCS. Springer, pp 398-416
    • (1999) LNCS , vol.1540 , pp. 398-416
    • Pasquier, N.1    Bastide, Y.2    Taouil, R.3    Lakhal, L.4
  • 74
    • 2842583711 scopus 로고
    • Raisonner avec des règles d'inférence graduelle - Une approche basée sur les ensembles flous
    • Prade H (1988) Raisonner avec des règles d'inférence graduelle - Une approche basée sur les ensembles flous. Revue d'Intelligence Artificielle 2(2):29-44
    • (1988) Revue D'Intelligence Artificielle , vol.2 , Issue.2 , pp. 29-44
    • Prade, H.1
  • 75
    • 0014534297 scopus 로고
    • A new approach to clustering
    • Ruspini EH (1969) A new approach to clustering. Inf Contr 15:22-32
    • (1969) Inf Contr , vol.15 , pp. 22-32
    • Ruspini, E.H.1
  • 84
    • 84974728129 scopus 로고    scopus 로고
    • Intelligent structuring and reducing of association rules with formal concept analysis
    • Proceedings of the 24th German conference on artificial intelligence. Springer-Verlag
    • Stumme G, Taouil R, Bastide Y, Pasquier N, Lakhal L (2001) Intelligent structuring and reducing of association rules with formal concept analysis. In: Proceedings of the 24th German conference on artificial intelligence, vol 2174 of LNCS. Springer-Verlag
    • (2001) LNCS , vol.2174
    • Stumme, G.1    Taouil, R.2    Bastide, Y.3    Pasquier, N.4    Lakhal, L.5
  • 85
    • 9644270327 scopus 로고    scopus 로고
    • Examples, counterexamples, and measuring fuzzy associations
    • Sudkamp T (2005) Examples, counterexamples, and measuring fuzzy associations. Fuzzy Sets Syst 149(1)
    • (2005) Fuzzy Sets Syst , vol.149 , Issue.1
    • Sudkamp, T.1
  • 91
    • 0018668763 scopus 로고
    • On the measure of fuzziness and negation-part I: Membership in the unit interval
    • Yager RR (1979) On the measure of fuzziness and negation-part I: Membership in the unit interval. Int J Gen Syst 5:221-229
    • (1979) Int J Gen Syst , vol.5 , pp. 221-229
    • Yager, R.R.1
  • 93
    • 0013341270 scopus 로고    scopus 로고
    • Discovering knowledge from fuzzy concept lattice
    • Kandel A, Last M, Bunke H (eds) Data mining and computational intelligence. Physica-Verlag
    • Yahia SB, Jaoua A (2001) Discovering knowledge from fuzzy concept lattice. In: Kandel A, Last M, Bunke H (eds) Data mining and computational intelligence, vol 68 of Studies in Fuzziness and Soft Computing. Physica-Verlag, pp 167-190
    • (2001) Studies in Fuzziness and Soft Computing , vol.68 , pp. 167-190
    • Yahia, S.B.1    Jaoua, A.2
  • 95
    • 34248666540 scopus 로고
    • Fuzzy sets
    • Zadeh LA (1965) Fuzzy sets. Inf Control 8:338-353
    • (1965) Inf Control , vol.8 , pp. 338-353
    • Zadeh, L.A.1
  • 96
    • 17044438212 scopus 로고    scopus 로고
    • Efficient algorithms for mining closed itemsets and their lattice structure
    • Zaki M, Hsiao CJ (2005) Efficient algorithms for mining closed itemsets and their lattice structure. IEEE Trans Knowl Data Eng 17(4):462-478
    • (2005) IEEE Trans Knowl Data Eng , vol.17 , Issue.4 , pp. 462-478
    • Zaki, M.1    Hsiao, C.J.2
  • 97
    • 0033718951 scopus 로고    scopus 로고
    • Scalable algorithms for association mining
    • Zaki MJ (2000) Scalable algorithms for association mining. IEEE Trans Knowl Data Eng 12(3):372-390
    • (2000) IEEE Trans Knowl Data Eng , vol.12 , Issue.3 , pp. 372-390
    • Zaki, M.J.1
  • 98
    • 0008396348 scopus 로고    scopus 로고
    • New algorithms for fast discovery of association rules
    • Computer Science Department, University of Rochester, Rochester, NY 14627
    • Zaki MJ, Parthasarathy S, Ogihara M, Li W (1997) New algorithms for fast discovery of association rules. Technical Report 651, Computer Science Department, University of Rochester, Rochester, NY 14627
    • (1997) Technical Report , vol.651
    • Zaki, M.J.1    Parthasarathy, S.2    Ogihara, M.3    Li, W.4


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