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Volumn 6732 LNCS, Issue , 2011, Pages 38-49

Latent clustering on graphs with multiple edge types

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING PROBLEMS; CLUSTERINGS; MODELING POWER; PARTIAL INFORMATION; SIMILARITY METRICS; SYNTHETIC DATA; FULL INFORMATIONS;

EID: 79958227880     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21286-4_4     Document Type: Conference Paper
Times cited : (8)

References (14)
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  • 3
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  • 6
    • 71849108522 scopus 로고    scopus 로고
    • Community detection algorithms: A comparative analysis
    • November doi:10.1103/PhysRevE.80.056117
    • Lancichinetti, A., Fortunato, S.: Community detection algorithms: A comparative analysis. Physical Review E 80(5) (November 2009), http://pre.aps.org.proxy.uchicago.edu/abstract/PRE/v80/i5/e056117, doi:10.1103/PhysRevE.80.056117
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    • Lancichinetti, A.1    Fortunato, S.2
  • 7
    • 2442611856 scopus 로고    scopus 로고
    • Stability-based validation of clustering solutions, neural computation
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    • Lange, T.1    Roth, V.2    Braun, M.L.3    Buhmann, J.M.4
  • 11
    • 77952328459 scopus 로고    scopus 로고
    • Community Structure in Time-Dependent, Multiscale, and Multiplex Networks
    • doi:10.1126/science.1184819
    • Mucha, P.J., Richardson, T., Macon, K., Porter, M.A., Onnela, J.P.: Community Structure in Time-Dependent, Multiscale, and Multiplex Networks. Science 328(5980), 876-878 (2010), http://www.sciencemag.org/content/328/5980/ 876.full, doi:10.1126/science.1184819
    • (2010) Science , vol.328 , Issue.5980 , pp. 876-878
    • Mucha, P.J.1    Richardson, T.2    Macon, K.3    Porter, M.A.4    Onnela, J.P.5
  • 12
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    • Computing an aggregate edge-weight function for clustering graphs with multiple edge types
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    • Rocklin, M., Pinar, A.: Computing an aggregate edge-weight function for clustering graphs with multiple edge types. In: Kumar, R., Sivakumar, D. (eds.) WAW2010. LNCS, vol. 6516, pp. 25-35. Springer, Heidelberg (2010)
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    • Cluster Ensembles A Knowledge Reuse Framework for Combining Multiple Partitions
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    • Strehl, A., Ghosh, J.: Cluster Ensembles A Knowledge Reuse Framework for Combining Multiple Partitions. Journal of Machine Learning Research 3(3), 583-617 (2003), http://www.crossref.org/jmlr-DOI.html, doi:10.1162/ 153244303321897735
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.