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Volumn , Issue , 2010, Pages

FPrep: Fuzzy clustering driven efficient automated pre-processing for fuzzy association Rule Mining

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULE MINING; BINARY VALUES; DATA SETS; FREQUENT ITEMSETS; FUZZY ASSOCIATION RULE; FUZZY ATTRIBUTES; FUZZY DATA; FUZZY PARTITION; FUZZY TECHNIQUES; FUZZY VERSION; HARD CLUSTERING; NUMERICAL VALUES; PARTITION BOUNDARY; PRE-PROCESSING; QUANTITATIVE VALUES; SHARP PARTITIONS; TRANSFORMATION TECHNIQUES;

EID: 78549263372     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2010.5584154     Document Type: Conference Paper
Times cited : (17)

References (22)
  • 2
    • 9644306576 scopus 로고    scopus 로고
    • Computationally efficient mining for fuzzy implication-based association rules in quantitative databases
    • Chen G., Yan P., Kerre E.E.: Computationally Efficient Mining for Fuzzy Implication-Based Association Rules in Quantitative Databases. International Journal of General Systems, 33, 163-182 (2004).
    • (2004) International Journal of General Systems , vol.33 , pp. 163-182
    • Chen, G.1    Yan, P.2    Kerre, E.E.3
  • 3
    • 26944491093 scopus 로고    scopus 로고
    • Fuzzy methods in machine learning and data mining: Status and prospects
    • Hüllermeier, E.: Fuzzy methods in machine learning and data mining: Status and prospects. Fuzzy Sets and Systems. 156, 387-406 (2005).
    • (2005) Fuzzy Sets and Systems. , vol.156 , pp. 387-406
    • Hüllermeier, E.1
  • 6
    • 9644252808 scopus 로고    scopus 로고
    • Elicitation of fuzzy association rules from positive and negative examples
    • De Cock, M., Cornelis, C., Kerre, E.E.: Elicitation of fuzzy association rules from positive and negative examples. Fuzzy Sets and Systems, 149, 73-85 (2005).
    • (2005) Fuzzy Sets and Systems , vol.149 , pp. 73-85
    • De Cock, M.1    Cornelis, C.2    Kerre, E.E.3
  • 8
    • 33748458842 scopus 로고    scopus 로고
    • A systematic approach to the assessment of fuzzy association rules
    • Dubois, D., Hüllermeier, E., Prade, H.: A systematic approach to the assessment of fuzzy association rules. Data Min. Knowl. Discov., 13, 167-192 (2006).
    • (2006) Data Min. Knowl. Discov. , vol.13 , pp. 167-192
    • Dubois, D.1    Hüllermeier, E.2    Prade, H.3
  • 11
    • 0027621699 scopus 로고
    • Mining association rules between sets of items in large databases
    • Agrawal, R., Imielinski, T., Swami, A.N.: Mining Association Rules between Sets of Items in Large Databases. SIGMOD Record, 22, 207-216 (1993).
    • (1993) SIGMOD Record , vol.22 , pp. 207-216
    • Agrawal, R.1    Imielinski, T.2    Swami, A.N.3
  • 13
    • 0039253846 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation
    • ACM Press
    • Han, J., Pei, J., Yin, Y.: Mining Frequent Patterns without Candidate Generation. In: SIGMOD Conference, pp. 1-12. ACM Press (2000).
    • (2000) SIGMOD Conference , pp. 1-12
    • Han, J.1    Pei, J.2    Yin, Y.3
  • 14
    • 2442449952 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation: A frequent-pattern tree approach.
    • Han, J., Pei, J., Yin, Y., Mao, R.: Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach. Data Mining and Knowledge Discovery, 8, 53-87 (2004).
    • (2004) Data Mining and Knowledge Discovery , vol.8 , pp. 53-87
    • Han, J.1    Pei, J.2    Yin, Y.3    Mao, R.4
  • 15
  • 16
    • 0015644825 scopus 로고
    • A fuzzy relative of the ISODATA process and its use in detecting compact well separated clusters
    • Dunn, J. C.: A Fuzzy Relative of the ISODATA Process and its Use in Detecting Compact, Well Separated Clusters. J. Cyber., 3, 32-57 (1974).
    • (1974) J. Cyber. , vol.3 , pp. 32-57
    • Dunn, J.C.1


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