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Volumn 18, Issue 1, 2009, Pages 61-81

One in a million: Picking the right patterns

Author keywords

Data mining; Pattern reduction; Post processing

Indexed keywords

HEURISTIC ALGORITHMS; TURING MACHINES;

EID: 58549089000     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-008-0136-4     Document Type: Article
Times cited : (33)

References (15)
  • 1
    • 33644513793 scopus 로고    scopus 로고
    • On condensed representations of constrained frequent patterns
    • Bonchi F, Lucchese C (2006) On condensed representations of constrained frequent patterns. Knowl Inf Syst 9:180-201
    • (2006) Knowl Inf Syst , vol.9 , pp. 180-201
    • Bonchi, F.1    Lucchese, C.2
  • 2
    • 57349086983 scopus 로고    scopus 로고
    • Recursion pruning for the apriori algorithm
    • In: Bayardo RJ Jr, Goethals B, Zaki MJ (eds) Brighton, UK, November 1, 2004. CEUR Worshop Proceedings, CEUR-WS.org
    • Borgelt C (2004) Recursion pruning for the apriori algorithm. In: Bayardo RJ Jr, Goethals B, Zaki MJ (eds) FIMI'04, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations, Brighton, UK, November 1, 2004. CEUR Worshop Proceedings, CEUR-WS.org, vol 126
    • (2004) FIMI'04, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations , vol.126
    • Borgelt, C.1
  • 3
    • 0034860134 scopus 로고    scopus 로고
    • Mining free itemsets under constraints
    • In: Adiba ME, Collet C, Desai BC (eds)
    • Boulicaut J-F, Jeudy B (2001) Mining free itemsets under constraints. In: Adiba ME, Collet C, Desai BC (eds) IDEAS, pp 322-329
    • (2001) IDEAS , pp. 322-329
    • Boulicaut, J.-F.1    Jeudy, B.2
  • 4
    • 33646417618 scopus 로고    scopus 로고
    • 2 - Decision trees for tree structured data
    • In: Jorge A, Torgo L, Brazdil P, Camacho R, Gama J(eds) Springer, Berlin
    • 2 - decision trees for tree structured data. In: Jorge A, Torgo L, Brazdil P, Camacho R, Gama J(eds) PKDD. Springer, Berlin, pp 46-58
    • (2005) PKDD , pp. 46-58
    • Bringmann, B.1    Zimmermann, A.2
  • 5
    • 84864832875 scopus 로고    scopus 로고
    • Mining all non-derivable frequent itemsets
    • In: Elomaa T, Mannila H, Toivonen H(eds) Springer, Berlin
    • Calders T, Goethals B (2002) Mining all non-derivable frequent itemsets. In: Elomaa T, Mannila H, Toivonen H(eds) PKDD. Springer, Berlin, pp 74-85
    • (2002) PKDD , pp. 74-85
    • Calders, T.1    Goethals, B.2
  • 6
    • 34547803269 scopus 로고    scopus 로고
    • Summarization - Compressing data into an informative representation
    • Chandola V, Kumar V (2007) Summarization - compressing data into an informative representation. Knowl Inf Syst 12:355-378
    • (2007) Knowl Inf Syst , vol.12 , pp. 355-378
    • Chandola, V.1    Kumar, V.2
  • 7
    • 26444454606 scopus 로고    scopus 로고
    • Feature selection for unsupervised learning
    • Dy JG, Brodley CE (2004) Feature selection for unsupervised learning. J Mach Learn Res 5:845-889
    • (2004) J Mach Learn Res , vol.5 , pp. 845-889
    • Dy, J.G.1    Brodley, C.E.2
  • 8
    • 33750321053 scopus 로고    scopus 로고
    • Pattern teams
    • In: Fürnkranz J, Scheffer T, Spiliopoulou M(eds) Springer, Berlin
    • Knobbe AJ, Ho EKY (2006) Pattern teams. In: Fürnkranz J, Scheffer T, Spiliopoulou M(eds) PKDD. Springer, Berlin, pp 577-584
    • (2006) PKDD , pp. 577-584
    • Knobbe, A.J.1    Ho, E.K.Y.2
  • 9
    • 58549101823 scopus 로고    scopus 로고
    • kfoil: Learning simple relational kernels
    • In: AAAI Press, Menlo Park
    • Landwehr N, Passerini A, Raedt LD, Frasconi P (2006) kfoil: Learning simple relational kernels. In: AAAI. AAAI Press, Menlo Park
    • (2006) AAAI
    • Landwehr, N.1    Passerini, A.2    Raedt, L.D.3    Frasconi, P.4
  • 10
    • 49749147619 scopus 로고    scopus 로고
    • Relevancy in constraint-based subgroup discovery
    • In: Boulicaut J-F, Raedt LD, Mannila H(eds) Springer, Berlin
    • Lavrac N, Gamberger D (2004) Relevancy in constraint-based subgroup discovery. In: Boulicaut J-F, Raedt LD, Mannila H(eds) Constraint-based mining and inductive databases. Springer, Berlin, pp 243-266
    • (2004) Constraint-Based Mining and Inductive Databases , pp. 243-266
    • Lavrac, N.1    Gamberger, D.2
  • 11
    • 0030643619 scopus 로고    scopus 로고
    • Clustering association rules
    • In: Gray WA, Larson P-Å (eds)
    • Lent B, Swami AN, Widom J (1997) Clustering association rules. In: Gray WA, Larson P-Å (eds) ICDE, pp 220-231
    • (1997) ICDE , pp. 220-231
    • Lent, B.1    Swami, A.N.2    Widom, J.3
  • 12
    • 21944442464 scopus 로고    scopus 로고
    • Levelwise search and borders of theories in knowledge discovery
    • Mannila H, Toivonen H (1997) Levelwise search and borders of theories in knowledge discovery. Data Min Knowl Discov 1(3):241-258
    • (1997) Data Min Knowl Discov , vol.1 , Issue.3 , pp. 241-258
    • Mannila, H.1    Toivonen, H.2
  • 13
    • 33745537736 scopus 로고    scopus 로고
    • Mining condensed frequent-pattern bases
    • Pei J, Dong G, Zou W, Han J (2004) Mining condensed frequent-pattern bases. Knowl Inf Syst 6:570-594
    • (2004) Knowl Inf Syst , vol.6 , pp. 570-594
    • Pei, J.1    Dong, G.2    Zou, W.3    Han, J.4
  • 14
    • 33750316546 scopus 로고    scopus 로고
    • Item sets that compress
    • In: Ghosh J, Lambert D, Skillicorn DB, Srivastava J(eds) SIAM, Philadelphia
    • Siebes A, Vreeken J, van Leeuwen M (2006) Item sets that compress. In: Ghosh J, Lambert D, Skillicorn DB, Srivastava J(eds) SDM. SIAM, Philadelphia
    • (2006) SDM
    • Siebes, A.1    Vreeken, J.2    van Leeuwen, M.3
  • 15
    • 0033905505 scopus 로고    scopus 로고
    • Mining bases for association rules using closed sets
    • Taouil R, Pasquier N, Bastide Y, Lakhal L (2000) Mining bases for association rules using closed sets. In: ICDE, p 307
    • (2000) ICDE , pp. 307
    • Taouil, R.1    Pasquier, N.2    Bastide, Y.3    Lakhal, L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.