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Volumn 22, Issue 9, 2010, Pages 1203-1218

Mining frequent subgraph patterns from uncertain graph data

Author keywords

algorithm; frequent subgraph pattern; Graph mining; uncertain graph

Indexed keywords

EFFICIENT METHOD; ERROR TOLERANCE; FREQUENT SUBGRAPHS; GRAPH DATA; GRAPH DATABASE; GRAPH MINING; MINING ALGORITHMS; NP-HARD; PATTERN MINING; PRUNING METHODS; REAL APPLICATIONS; SUBGRAPHS;

EID: 77955171415     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2010.80     Document Type: Article
Times cited : (137)

References (46)
  • 2
    • 46749134436 scopus 로고    scopus 로고
    • Discovering functional interaction patterns in protein-protein interaction networks
    • M.E. Turanalp and T. Can, "Discovering Functional Interaction Patterns in Protein-Protein Interaction Networks," BMC Bioinformatics, vol.9, no.1, p. 276, 2008.
    • (2008) BMC Bioinformatics , vol.9 , Issue.1 , pp. 276
    • Turanalp, M.E.1    Can, T.2
  • 3
    • 33747586075 scopus 로고    scopus 로고
    • A direct comparison of protein interaction confidence assignment schemes
    • S. Suthram, T. Shlomi, E. Ruppin, R. Sharan, and T. Ideker, "A Direct Comparison of Protein Interaction Confidence Assignment Schemes," BMC Bioinformatics, vol.7, no.1, p. 360, 2006.
    • (2006) BMC Bioinformatics , vol.7 , Issue.1 , pp. 360
    • Suthram, S.1    Shlomi, T.2    Ruppin, E.3    Sharan, R.4    Ideker, T.5
  • 4
    • 3042523388 scopus 로고    scopus 로고
    • Predicting protein complex membership using probabilistic network reliability
    • S. Asthana, O.D. King, F.D. Gibbons, and F.P. Roth, "Predicting Protein Complex Membership Using Probabilistic Network Reliability," Genome Research, vol.14, no.6, pp. 1170-1175, 2004.
    • (2004) Genome Research , vol.14 , Issue.6 , pp. 1170-1175
    • Asthana, S.1    King, O.D.2    Gibbons, F.D.3    Roth, F.P.4
  • 7
    • 34548329908 scopus 로고    scopus 로고
    • On a routing problem within probabilistic graphs and its application to intermittently connected networks
    • J. Ghosh, H.Q. Ngo, S. Yoon, C. Qiao, "On a Routing Problem Within Probabilistic Graphs and Its Application to Intermittently Connected Networks," Proc. Int'l Conf. Computer Comm., 2007.
    • (2007) Proc. Int'l Conf. Computer Comm.
    • Ghosh, J.1    Ngo, H.Q.2    Yoon, S.3    Qiao, C.4
  • 8
    • 14844305006 scopus 로고    scopus 로고
    • An efficient algorithm for detecting frequent subgraphs in biological networks
    • M. Koyutürk, A. Grama, and W. Szpankowski, "An Efficient Algorithm for Detecting Frequent Subgraphs in Biological Networks," Bioinformatics, vol. 20, no. Suppl. 1, pp. i200-i207, 2004.
    • (2004) Bioinformatics , vol.20 , Issue.SUPPL. 1
    • Koyutürk, M.1    Grama, A.2    Szpankowski, W.3
  • 11
    • 49249151236 scopus 로고
    • The complexity of computing the permanent
    • L.G. Valiant, "The Complexity of Computing the Permanent," Theoretical Computer Science, vol.8, pp. 189-201, 1979.
    • (1979) Theoretical Computer Science , vol.8 , pp. 189-201
    • Valiant, L.G.1
  • 13
  • 14
    • 78149328300 scopus 로고    scopus 로고
    • Efficient mining of frequent subgraphs in the presence of isomorphism
    • J. Huan, W. Wang, and J. Prins, "Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism," Proc. Int'l Conf. Data Mining, 2003.
    • (2003) Proc. Int'l Conf. Data Mining
    • Huan, J.1    Wang, W.2    Prins, J.3
  • 15
    • 12244294066 scopus 로고    scopus 로고
    • A quickstart in frequent structure mining can make a difference
    • S. Nijssen and J.N. Kok, "A Quickstart in Frequent Structure Mining Can Make a Difference," Proc. ACM SIGKDD Conf., 2004.
    • (2004) Proc. ACM SIGKDD Conf.
    • Nijssen, S.1    Kok, J.N.2
  • 16
    • 85008016154 scopus 로고    scopus 로고
    • Discovering frequent graph patterns using disjoint paths
    • Nov.
    • N. Vanetik, "Discovering Frequent Graph Patterns Using Disjoint Paths," IEEE Trans. Knowledge and Data Eng., vol.18, no.11, pp. 1441-1456, Nov. 2006.
    • (2006) IEEE Trans. Knowledge and Data Eng. , vol.18 , Issue.11 , pp. 1441-1456
    • Vanetik, N.1
  • 20
    • 77952334885 scopus 로고    scopus 로고
    • Closegraph: Mining closed frequent graph patterns
    • X. Yan and J. Han, "Closegraph: Mining Closed Frequent Graph Patterns," Proc. ACM SIGKDD Conf., 2003.
    • (2003) Proc. ACM SIGKDD Conf.
    • Yan, X.1    Han, J.2
  • 24
    • 33749600907 scopus 로고    scopus 로고
    • Clan: An algorithm for mining closed cliques from large dense graph databases
    • J. Wang, Z. Zeng, and L. Zhou, "Clan: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases," Proc. Int'l Conf. Data Eng., 2006.
    • (2006) Proc. Int'l Conf. Data Eng.
    • Wang, J.1    Zeng, Z.2    Zhou, L.3
  • 25
    • 34547455408 scopus 로고    scopus 로고
    • Out-of-core coherent closed quasi-clique mining from large dense graph databases
    • Z. Zeng, J. Wang, L. Zhou, and G. Karypis, "Out-of-Core Coherent Closed Quasi-Clique Mining from Large Dense Graph Databases," ACM Trans. Database Systems, vol.32, no.2, p. 13, 2007.
    • (2007) ACM Trans. Database Systems , vol.32 , Issue.2 , pp. 13
    • Zeng, Z.1    Wang, J.2    Zhou, L.3    Karypis, G.4
  • 30
    • 67649644367 scopus 로고    scopus 로고
    • Graphsig: A scalable approach to mining significant subgraphs in large graph databases
    • S. Ranu and A.K. Singh, "GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases," Proc. Int'l Conf. Data Eng., 2009.
    • (2009) Proc. Int'l Conf. Data Eng.
    • Ranu, S.1    Singh, A.K.2
  • 36
  • 43
    • 34547302157 scopus 로고    scopus 로고
    • On the maximum number of cliques in a graph
    • D.R. Wood, "On the Maximum Number of Cliques in a Graph," Graphs and Combinatorics, vol.23, no.3, pp. 337-352, 2007.
    • (2007) Graphs and Combinatorics , vol.23 , Issue.3 , pp. 337-352
    • Wood, D.R.1
  • 46
    • 77955172510 scopus 로고    scopus 로고
    • COG functions, http://www.ncbi.nlm.nih.gov/COG/, 2010.
    • COG Functions , vol.2010


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.