메뉴 건너뛰기




Volumn 17, Issue 11, 2005, Pages 1490-1504

MAFIA: A maximal frequent itemset algorithm

Author keywords

Itemset mining; Maximal itemsets; Transactional databases

Indexed keywords

DATA SETS; ITEMSET MINING; MAXIMAL ITEMSETS; TRANSACTIONAL DATABASES;

EID: 28244494064     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2005.183     Document Type: Article
Times cited : (222)

References (38)
  • 1
    • 0031162961 scopus 로고    scopus 로고
    • Dynamic itemset counting and implication rules for market basket data
    • J. Peckham, ed., citeseer.nj.nec.com/brin97dynamic.html
    • S. Brin, R. Motwani, J.D. Ullman, and S. Tsur, "Dynamic Itemset Counting and Implication Rules for Market Basket Data," Proc. ACM SIGMOD Int'l Conf. Management of Data, J. Peckham, ed., pp. 255-264, 1997, citeseer.nj.nec.com/brin97dynamic.html.
    • (1997) Proc. ACM SIGMOD Int'l Conf. Management of Data , pp. 255-264
    • Brin, S.1    Motwani, R.2    Ullman, J.D.3    Tsur, S.4
  • 2
    • 85084163349 scopus 로고    scopus 로고
    • Data mining approaches for intrusion detection
    • citeseer.nj.nec.com/article/lee00data.html
    • W. Lee and S. Stolfo, "Data Mining Approaches for Intrusion Detection," Proc. Seventh USENIX Security Symp., 1998, citeseer.nj.nec.com/ article/lee00data.html.
    • (1998) Proc. Seventh USENIX Security Symp.
    • Lee, W.1    Stolfo, S.2
  • 4
    • 0027621699 scopus 로고
    • Mining association rules between sets of items in large databases
    • P. Buneman and S. Jajodia, eds., citeseer.nj.nec.com/agrawal93mining. html.
    • R. Agrawal, T. Imielinski, and A.N. Swami, "Mining Association Rules between Sets of Items in Large Databases," Proc. ACM SIGMOD Int'l Conf. Management of Data, P. Buneman and S. Jajodia, eds., pp. 207-216, 1993, citeseer.nj.nec.com/agrawal93mining.html.
    • (1993) Proc. ACM SIGMOD Int'l Conf. Management of Data , pp. 207-216
    • Agrawal, R.1    Imielinski, T.2    Swami, A.N.3
  • 5
    • 0001882616 scopus 로고
    • Fast algorithms for mining association rules
    • J. B. Bocca, M. Jarke, and C. Zaniolo, eds., citeseer.nj.nec.com/ agrawal94fast.html
    • R. Agrawal and R. Srikant, "Fast Algorithms for Mining Association Rules," Proc. 20th Int'l Conf. Very Large Data Bases, J. B. Bocca, M. Jarke, and C. Zaniolo, eds., pp. 487-499, 1994, citeseer.nj.nec.com/ agrawal94fast.html.
    • (1994) Proc. 20th Int'l Conf. Very Large Data Bases , pp. 487-499
    • Agrawal, R.1    Srikant, R.2
  • 7
    • 0031699077 scopus 로고    scopus 로고
    • Mining association rules: Anti-skew algorithms
    • citeseer.ist.psu.edu/lin98mining.html
    • J. Lin and M.H. Dunham, "Mining Association Rules: Anti-Skew Algorithms," Proc. 14th Int'l Conf. Data Eng., pp. 486-493, 1998, citeseer.ist.psu.edu/lin98mining.html.
    • (1998) Proc. 14th Int'l Conf. Data Eng. , pp. 486-493
    • Lin, J.1    Dunham, M.H.2
  • 8
    • 0031675159 scopus 로고    scopus 로고
    • Mining optimized association rules with categorical and numeric attributes
    • citeseer.nj.nec.com/article/rastogi98mining.html
    • R. Rastogi and K. Shim, "Mining Optimized Association Rules with Categorical and Numeric Attributes," Proc. 14th Int'l Conf. Data Eng., pp. 503-512, 1998, citeseer.nj.nec.com/article/rastogi98mining.html.
    • (1998) Proc. 14th Int'l Conf. Data Eng. , pp. 503-512
    • Rastogi, R.1    Shim, K.2
  • 9
    • 0031270195 scopus 로고    scopus 로고
    • Mining generalized association rules
    • citeseer.nj.nec.com/srikant95mining.html
    • R. Srikant and R. Agrawal, "Mining Generalized Association Rules," Future Generation Computer Systems, vol. 13, nos. 2-3, pp. 161-180, 1997, citeseer.nj.nec.com/srikant95mining.html.
    • (1997) Future Generation Computer Systems , vol.13 , Issue.2-3 , pp. 161-180
    • Srikant, R.1    Agrawal, R.2
  • 10
    • 22044433094 scopus 로고    scopus 로고
    • Mining frequent itemsets using support constraints
    • citeseer.nj.nec.com/wang00mining.html
    • K. Wang, Y. He, and J. Han, "Mining Frequent Itemsets Using Support Constraints," Proc. 26th Int'l Conf. Very Large Databases, pp. 43-52, 2000, citeseer.nj.nec.com/wang00mining.html.
    • (2000) Proc. 26th Int'l Conf. Very Large Databases , pp. 43-52
    • Wang, K.1    He, Y.2    Han, J.3
  • 11
    • 0000835392 scopus 로고
    • Opus: An efficient admissible algorithm for unordered search
    • citeseer.nj.nec.com/35589.html
    • G.I. Webb, "Opus: An Efficient Admissible Algorithm for Unordered Search," J. Artificial Intelligence Research, vol. 3, pp. 431-465, 1995, citeseer.nj.nec.com/35589.html.
    • (1995) J. Artificial Intelligence Research , vol.3 , pp. 431-465
    • Webb, G.I.1
  • 12
    • 84911977993 scopus 로고    scopus 로고
    • Discovering frequent closed itemsets for association rules dude!
    • citeseer.nj.nec.com/pasquier99discovering.html
    • N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, "Discovering Frequent Closed Itemsets for Association Rules Dude!" Lecture Notes in Computer Science, vol. 1540, pp. 398-416, 1999, citeseer.nj.nec.com/ pasquier99discovering.html.
    • (1999) Lecture Notes in Computer Science , vol.1540 , pp. 398-416
    • Pasquier, N.1    Bastide, Y.2    Taouil, R.3    Lakhal, L.4
  • 14
    • 0004107776 scopus 로고    scopus 로고
    • Charm: An efficient algorithm for closed association rule mining
    • RPI, citeseer.nj.nec.com/zaki99charm.html
    • M. Zaki and C. Hsiao, "Charm: An Efficient Algorithm for Closed Association Rule Mining," technical report, RPI, 1999, citeseer.nj.nec.com/ zaki99charm.html,
    • (1999) Technical Report
    • Zaki, M.1    Hsiao, C.2
  • 16
    • 0031684427 scopus 로고    scopus 로고
    • Combinatorial pattern discovery in biological sequences: The teiresias algorithm
    • I. Rigoutsos and A. Floratos, "Combinatorial Pattern Discovery in Biological Sequences: The Teiresias Algorithm," Bioinformatics, vol. 14, no. 1, pp. 55-67, 1998.
    • (1998) Bioinformatics , vol.14 , Issue.1 , pp. 55-67
    • Rigoutsos, I.1    Floratos, A.2
  • 18
    • 0003132261 scopus 로고    scopus 로고
    • Mining large itemsets for association rules
    • citeseer.nj.nec.com/aggarwal98mining.html
    • C.C. Aggarwal and P.S. Yu, "Mining Large Itemsets for Association Rules," Bull. IEEE CS Technical Comittee Data Eng., vol. 21, no. 1, pp. 23-31, 1998, citeseer.nj.nec.com/aggarwal98mining.html.
    • (1998) Bull. IEEE CS Technical Comittee Data Eng. , vol.21 , Issue.1 , pp. 23-31
    • Aggarwal, C.C.1    Yu, P.S.2
  • 19
    • 0031649139 scopus 로고    scopus 로고
    • Online generation of association rules
    • citeseer.nj.nec.com/aggarwal98online.html
    • "Online Generation of Association Rules," Proc. 14th Int'l Conf. Data Eng., pp. 402-411, 1998, citeseer.nj.nec.com/aggarwal98online.html.
    • (1998) Proc. 14th Int'l Conf. Data Eng. , pp. 402-411
  • 20
    • 0032671296 scopus 로고    scopus 로고
    • Data organization and access for efficient data mining
    • citeseer.nj.nec.com/dunkel99data.html
    • B. Dunkel and N. Soparkar, "Data Organization and Access for Efficient Data Mining," Proc. 15th Int'l Conf. Data Eng. (ICDE), pp. 522-529, 1999, citeseer.nj.nec.com/dunkel99data.html.
    • (1999) Proc. 15th Int'l Conf. Data Eng. (ICDE) , pp. 522-529
    • Dunkel, B.1    Soparkar, N.2
  • 21
    • 0035053182 scopus 로고    scopus 로고
    • Demon: Mining and monitoring evolving data
    • citeseer.nj.nec.com/ganti00demon.html.
    • V. Ganti, J. Gehrke, and R. Ramakrishnan, "Demon: Mining and Monitoring Evolving Data," IEEE Trans. Knowledge and Data Eng., vol. 13, no. 1, pp. 50-63, 2001, citeseer.nj.nec.com/ganti00demon.html.
    • (2001) IEEE Trans. Knowledge and Data Eng. , vol.13 , Issue.1 , pp. 50-63
    • Ganti, V.1    Gehrke, J.2    Ramakrishnan, R.3
  • 22
    • 0039253846 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation
    • citeseer.nj.nec.com/article/han99mining.html
    • J. Han, J. Pei, and Y. Yin, "Mining Frequent Patterns without Candidate Generation," Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 1-12, 2000, citeseer.nj.nec.com/article/han99mining.html.
    • (2000) Proc. ACM SIGMOD Int'l Conf. Management of Data , pp. 1-12
    • Han, J.1    Pei, J.2    Yin, Y.3
  • 23
    • 84976830511 scopus 로고
    • An effective hash-based algorithm for mining association rules
    • M.J. Carey and D.A. Schneider, eds., citeseer.nj.nec.com/park95effective. html
    • J.S. Park, M.-S. Chen, and P.S. Yu, "An Effective Hash-Based Algorithm for Mining Association Rules," Proc. ACM SIGMOD Int'l Conf. Management of Data, M.J. Carey and D.A. Schneider, eds., pp. 175-186, 1995, citeseer.nj.nec.com/park95effective.html.
    • (1995) Proc. ACM SIGMOD Int'l Conf. Management of Data , pp. 175-186
    • Park, J.S.1    Chen, M.-S.2    Yu, P.S.3
  • 24
    • 0002082857 scopus 로고
    • An efficient algorithm for mining association rules in large databases
    • citeseer.nj.nec.com/sarasere95efficient.html
    • A. Savasere, E. Omiecinski, and S.B. Navathe, "An Efficient Algorithm for Mining Association Rules in Large Databases," Proc. 21st Int'l Conf. Very Large Databases, pp. 432-444, 1995, citeseer.nj.nec.com/ sarasere95efficient.html.
    • (1995) Proc. 21st Int'l Conf. Very Large Databases , pp. 432-444
    • Savasere, A.1    Omiecinski, E.2    Navathe, S.B.3
  • 26
    • 0002663969 scopus 로고    scopus 로고
    • Sampling large databases for association rules
    • T.M. Vijayaraman, A.P. Buchmann, C. Mohan, and N.L. Sarda, eds., citeseer.nj.nec.com/toivonen96sampling.html
    • H. Toivonen, "Sampling Large Databases for Association Rules," Proc. 22nd Int'l Conf. Very Large Databases, T.M. Vijayaraman, A.P. Buchmann, C. Mohan, and N.L. Sarda, eds., pp. 134-145, 1996, citeseer.nj.nec.com/ toivonen96sampling.html.
    • (1996) Proc. 22nd Int'l Conf. Very Large Databases , pp. 134-145
    • Toivonen, H.1
  • 27
  • 28
    • 0141764033 scopus 로고    scopus 로고
    • A tree projection algorithm for generation of frequent item sets
    • citeseer.nj.nec.com/agarwal99tree.html
    • R.C. Agarwal, C.C. Aggarwal, and V.V.V. Prasad, "A Tree Projection Algorithm for Generation of Frequent Item Sets," J. Parallel and Distributed Computing, vol. 61, no. 3, pp. 350-371, 2001, citeseer.nj.nec.com/ agarwal99tree.html.
    • (2001) J. Parallel and Distributed Computing , vol.61 , Issue.3 , pp. 350-371
    • Agarwal, R.C.1    Aggarwal, C.C.2    Prasad, V.V.V.3
  • 29
    • 84948968508 scopus 로고    scopus 로고
    • Discovering all most specific sentences by randomized algorithms
    • citeseer.nj.nec.com/gunopulos97discovering.html
    • D. Gunopulos, H. Mannila, and S. Saluja, "Discovering All Most Specific Sentences by Randomized Algorithms," Proc. Int'l Conf. Database Theory, pp. 215-229, 1997, citeseer.nj.nec.com/gunopulos97discovering.html.
    • (1997) Proc. Int'l Conf. Database Theory , pp. 215-229
    • Gunopulos, D.1    Mannila, H.2    Saluja, S.3
  • 30
    • 84890521199 scopus 로고    scopus 로고
    • Pincer search: A new algorithm for discovering the maximum frequent set
    • citeseer.nj.nec.com/lin98pincersearch.html
    • D.-I. Lin and Z.M. Kedem, "Pincer Search: A New Algorithm for Discovering the Maximum Frequent Set," Proc. Sixth European Conf. Extending Database Technology, pp. 105-119, 1998, citeseer.nj.nec.com/lin98pincersearch. html.
    • (1998) Proc. Sixth European Conf. Extending Database Technology , pp. 105-119
    • Lin, D.-I.1    Kedem, Z.M.2
  • 31
    • 0033718951 scopus 로고    scopus 로고
    • Scalable algorithms for association mining
    • M.J. Zaki, "Scalable Algorithms for Association Mining," IEEE Trans. Knowledge and Data Eng., vol. 12, pp. 372-390, 2000.
    • (2000) IEEE Trans. Knowledge and Data Eng. , vol.12 , pp. 372-390
    • Zaki, M.J.1
  • 33
    • 0035007850 scopus 로고    scopus 로고
    • Mafia: A maximal frequent itemset algorithm for transactional databases
    • D. Burdick, M. Calimlim, and J. Gehrke, "Mafia: A Maximal Frequent Itemset Algorithm for Transactional Databases," Proc. 17th Int'l Conf. Data Eng., pp. 443-452, 2001, http://www.cs.cornell.edu/johannes/papers/2001/ icde2001-mafia.pdf.
    • (2001) Proc. 17th Int'l Conf. Data Eng. , pp. 443-452
    • Burdick, D.1    Calimlim, M.2    Gehrke, J.3
  • 35
    • 78149351437 scopus 로고    scopus 로고
    • Efficiently mining maximal frequent itemsets
    • citeseer.nj.nec.com/499930.html
    • K. Gouda and M.J. Zaki, "Efficiently Mining Maximal Frequent Itemsets," Proc. IEEE Int'l Conf. Data Mining, pp. 163-170, 2001, citeseer.nj.nec.com/499930.html.
    • (2001) Proc. IEEE Int'l Conf. Data Mining , pp. 163-170
    • Gouda, K.1    Zaki, M.J.2
  • 36
    • 0001880210 scopus 로고    scopus 로고
    • Kdd-cup 2000 organizers' report: Peeling the onion
    • R. Kohavi, C. Brodley, B. Frasca, L. Mason, and Z. Zheng, "Kdd-Cup 2000 Organizers' Report: Peeling the Onion," SIGKDD Explorations, vol. 2, no. 2, pp. 86-98, 2000, http://www.ecn.purdue.edu/KDDCUP.
    • (2000) SIGKDD Explorations , vol.2 , Issue.2 , pp. 86-98
    • Kohavi, R.1    Brodley, C.2    Frasca, B.3    Mason, L.4    Zheng, Z.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.