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Volumn 4, Issue 3, 2010, Pages

Margin: Maximal frequent subgraph mining

Author keywords

Graph mining; Maximal frequent subgraph mining

Indexed keywords

CANDIDATE PATTERNS; EXPONENTIAL NUMBERS; FREQUENT SUBGRAPH MINING; FREQUENT SUBGRAPHS; GRAPH MINING; PROOF OF CORRECTNESS; SEARCH SPACES; SUBGRAPH MINING; SUBGRAPHS;

EID: 78049342020     PISSN: 15564681     EISSN: 1556472X     Source Type: Journal    
DOI: 10.1145/1839490.1839491     Document Type: Article
Times cited : (65)

References (51)
  • 4
    • 24044517207 scopus 로고    scopus 로고
    • Frequent subtree mining-an overview
    • CHI, Y., MUNTZ, R. R., NIJSSEN, S., AND KOK, J. N. 2005a. Frequent subtree mining-an overview. Fund. Informatics 66, 1-2, 161-198.
    • (2005) Fund. Informatics , vol.66 , Issue.1-2 , pp. 161-198
    • Chi, Y.1    Muntz, R.R.2    Nijssen, S.3    Kok, J.N.4
  • 5
    • 14644411753 scopus 로고    scopus 로고
    • Mining closed and maximal frequent subtrees from databases of labeled rooted trees
    • CHI, Y., XIA, Y., YANG, Y., AND MUNTZ, R. R. 2005b. Mining closed and maximal frequent subtrees from databases of labeled rooted trees. IEEE Trans. Knowl. Data Eng. 17, 190-202.
    • (2005) IEEE Trans. Knowl. Data Eng , vol.17 , pp. 190-202
    • Chi, Y.1    Xia, Y.2    Yang, Y.3    Muntz, R.R.4
  • 8
    • 0027652468 scopus 로고
    • Substructure discovery using minimum description length and background knowledge
    • COOK, D. J. AND HOLDER, L. B. 1994. Substructure discovery using minimum description length and background knowledge. J. Artif. Intell. Res. 1, 231-255.
    • (1994) J. Artif. Intell. Res. , vol.1 , pp. 231-255
    • Cook, D.J.1    Holder, L.B.2
  • 11
    • 78049353284 scopus 로고    scopus 로고
    • GSPAN. gspan Software
    • GSPAN. gspan Software. http://www.xifengyan. net/software/gSpan.htm.
  • 12
    • 78049329542 scopus 로고    scopus 로고
    • GTL. Graph Template Library
    • GTL. Graph Template Library. http://www.infosun. fmi.uni-passau.de/GTL/.
  • 19
    • 78049334443 scopus 로고    scopus 로고
    • IGRAPH. igraph Library
    • IGRAPH. igraph Library. http://igraph.sourceforge.net/.
  • 20
    • 84974733299 scopus 로고    scopus 로고
    • An apriori-based algorithm for mining frequent substructures from graph data
    • INOKUCHI, A., WASHIO, T., AND MOTODA, H. 2000. An apriori-based algorithm for mining frequent substructures from graph data. PKDD, 13-23.
    • (2000) PKDD , pp. 13-23
    • Inokuchi, A.1    Washio, T.2    Motoda, H.3
  • 24
    • 14844305006 scopus 로고    scopus 로고
    • An efficient algorithm for detecting frequent subgraphs in biological networks
    • KOYUTURK, M., GRAMA, A., AND SZPANKOWSKI, W. 2004. An efficient algorithm for detecting frequent subgraphs in biological networks. ISMB, 200-207.
    • (2004) ISMB , pp. 200-207
    • Koyuturk, M.1    Grama, A.2    Szpankowski, W.3
  • 25
    • 27944453480 scopus 로고    scopus 로고
    • Finding frequent patterns in a large sparse graph
    • KURAMOCHI, M. AND KARYPIS, G. 2005. Finding frequent patterns in a large sparse graph. Data Min. Knowl. Discov. 11, 243-271.
    • (2005) Data Min. Knowl. Discov. , vol.11 , pp. 243-271
    • Kuramochi, M.1    Karypis, G.2
  • 28
    • 78049323685 scopus 로고    scopus 로고
    • LIBGTOP. Unix Libgtop Utility
    • LIBGTOP. Unix Libgtop Utility. http://library.gnome.org/devel/libgtop/ stable/libgtop-GlibTop.html.
  • 35
    • 78049336119 scopus 로고    scopus 로고
    • TOP. Unix Top Utility, Unix
    • TOP. Unix Top Utility. http://en. wikipedia.org/wiki/Top (Unix).
  • 36
    • 78049321211 scopus 로고    scopus 로고
    • UCI KDD ARCHIVE. Anonymous web data of msnbc.com
    • UCI KDD ARCHIVE. Anonymous web data of msnbc.com. http://kdd.ics.uci.edu/ databases/msnbc/msnbc.html.
  • 39
    • 33749600907 scopus 로고    scopus 로고
    • CLAN: An algorithm for mining closed cliques from large dense graph databases
    • DOI 10.1109/ICDE.2006.34, 1617441, Proceedings of the 22nd International Conference on Data Engineering, ICDE '06
    • WANG, J., ZENG, Z., AND ZHOU, L. 2006b. Clan: An algorithm for mining closed cliques from large dense graph databases. In Proceedings of the IEEE International Conference on Data Engineering (ICDE). 73. (Pubitemid 44539865)
    • (2006) Proceedings - International Conference on Data Engineering , vol.2006 , pp. 73
    • Wang, J.1    Zeng, Z.2    Zhou, L.3
  • 40
    • 12244307653 scopus 로고    scopus 로고
    • State of the art of graph-based data mining
    • WASHIO, T. AND MOTODA, H. 2003. State of the art of graph-based data mining. SIGKDD Explorations, 5, 59-68.
    • (2003) SIGKDD Explorations , vol.5 , pp. 59-68
    • Washio, T.1    Motoda, H.2
  • 42
    • 78049331044 scopus 로고    scopus 로고
    • Yahoo Finance Stock Data
    • YAHOO FINANCE. Yahoo Finance Stock Data. http://finance.yahoo.com/.
    • Yahoo, F.1
  • 45
    • 3142736597 scopus 로고    scopus 로고
    • Graph indexing: A frequent structure-based approach
    • YAN, X., YU, P. S., AND HAN, J. 2004. Graph indexing: A frequent structure-based approach. SIGMOD, 335-346.
    • (2004) SIGMOD , pp. 335-346
    • Yan, X.1    Yu, P.S.2    Han, J.3
  • 47
    • 0028460882 scopus 로고
    • Graph-based induction as a unified learning framework
    • YOSHIDA, K., MOTODA, H., AND INDURKHYA, N. 1994. Graph-based induction as a unified learning framework. J. Applied Intel. 4, 297-328.
    • (1994) J. Applied Intel , vol.4 , pp. 297-328
    • Yoshida, K.1    Motoda, H.2    Indurkhya, N.3
  • 49
    • 2442629149 scopus 로고    scopus 로고
    • Charm: An efficient algorithm for closed itemset mining
    • ZAKI, M. J. AND HSIAO, C.-J. 2002. Charm: An efficient algorithm for closed itemset mining. SDM.
    • (2002) SDM
    • Zaki, M.J.1    Hsiao, C.-J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.