Spectral methods for graph clustering – A survey
Graph clustering is an area in cluster analysis that looks for groups of related vertices in a graph. Due to its large applicability, several graph clustering algorithms have been proposed in the last years. A particular class of graph clustering algorithms is known as spectral clustering algorithms...
Gespeichert in:
| Veröffentlicht in: | European journal of operational research Jg. 211; H. 2; S. 221 - 231 |
|---|---|
| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Amsterdam
Elsevier B.V
01.06.2011
Elsevier Elsevier Sequoia S.A |
| Schriftenreihe: | European Journal of Operational Research |
| Schlagworte: | |
| ISSN: | 0377-2217, 1872-6860 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Graph clustering is an area in cluster analysis that looks for groups of related vertices in a graph. Due to its large applicability, several graph clustering algorithms have been proposed in the last years. A particular class of graph clustering algorithms is known as spectral clustering algorithms. These algorithms are mostly based on the eigen-decomposition of Laplacian matrices of either weighted or unweighted graphs. This survey presents different graph clustering formulations, most of which based on graph cut and partitioning problems, and describes the main spectral clustering algorithms found in literature that solve these problems. |
|---|---|
| AbstractList | Graph clustering is an area in cluster analysis that looks for groups of related vertices in a graph. Due to its large applicability, several graph clustering algorithms have been proposed in the last years. A particular class of graph clustering algorithms is known as spectral clustering algorithms. These algorithms are mostly based on the eigen-decomposition of Laplacian matrices of either weighted or unweighted graphs. This survey presents different graph clustering formulations, most of which based on graph cut and partitioning problems, and describes the main spectral clustering algorithms found in literature that solve these problems. [PUBLICATION ABSTRACT] Graph clustering is an area in cluster analysis that looks for groups of related vertices in a graph. Due to its large applicability, several graph clustering algorithms have been proposed in the last years. A particular class of graph clustering algorithms is known as spectral clustering algorithms. These algorithms are mostly based on the eigen-decomposition of Laplacian matrices of either weighted or unweighted graphs. This survey presents different graph clustering formulations, most of which based on graph cut and partitioning problems, and describes the main spectral clustering algorithms found in literature that solve these problems. |
| Author | Nascimento, Mariá C.V. de Carvalho, André C.P.L.F. |
| Author_xml | – sequence: 1 givenname: Mariá C.V. surname: Nascimento fullname: Nascimento, Mariá C.V. email: mariah@icmc.usp.br – sequence: 2 givenname: André C.P.L.F. surname: de Carvalho fullname: de Carvalho, André C.P.L.F. email: andre@icmc.usp.br |
| BackLink | http://www.econis.eu/PPNSET?PPN=654683395$$DView this record in ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23897471$$DView record in Pascal Francis http://econpapers.repec.org/article/eeeejores/v_3a211_3ay_3a2011_3ai_3a2_3ap_3a221-231.htm$$DView record in RePEc |
| BookMark | eNp9ks2KFDEQx4Os4OzqC3ixEQQvPSaVzkeDl2VxVVzwoJ5DJl29k6an0ybdA3Pbd_ANfZJNO6PIHjaQVBF-__pI5ZycDWFAQl4yumaUyXfdGrsQ10DzBdVryuAJWTGtoJRa0jOyolypEoCpZ-Q8pY5SygQTKwLfRnRTtH2xw2kbmlS0IRa30Y7bwvVzmjD64bb4fferuCzSHPd4eE6etrZP-OJkL8iP6w_frz6VN18_fr66vCmdBD6VG76pnagcFxaUs9zyFhgVqDjnTa1cRVHV0mJrEVBJRRsL9WajLdKWITh-Qd4e444x_JwxTWbnk8O-twOGOZnceC1rJiqW0dcP0C7MccjVGS1ACglsgb4coYi5ZzNGv7PxYDCv_HaYzN5wm8F8HhaP_nH94uY9LhaYAc7MdtrlaG9OKW1ytm-jHZxP_6IC17Wq1JL11ZFDF4b_ACkqqTmvRSb0kXAxpBSxNc5PdvJhyHPxfe5zaVWazix1mmXGhmqTZ5yl8ED6N_yjovenivLw9h6jSc7j4LDxMf8F0wT_mPwe_Z-_aw |
| CODEN | EJORDT |
| CitedBy_id | crossref_primary_10_1109_LES_2022_3209137 crossref_primary_10_1371_journal_pone_0300358 crossref_primary_10_1038_s41598_018_21532_5 crossref_primary_10_4028_www_scientific_net_AMR_1037_422 crossref_primary_10_1111_mice_13203 crossref_primary_10_1002_sim_7928 crossref_primary_10_1007_s10115_012_0547_0 crossref_primary_10_1109_ACCESS_2017_2769484 crossref_primary_10_1109_TSP_2014_2314063 crossref_primary_10_3389_fimag_2024_1443142 crossref_primary_10_3390_math11030720 crossref_primary_10_1007_s10587_016_0281_y crossref_primary_10_1093_comnet_cnab016 crossref_primary_10_1109_TPAMI_2021_3056510 crossref_primary_10_1109_TQE_2021_3140190 crossref_primary_10_1016_j_knosys_2018_09_001 crossref_primary_10_1109_TGRS_2019_2913004 crossref_primary_10_3390_pr9030439 crossref_primary_10_1080_0740817X_2014_1001927 crossref_primary_10_1016_j_ijar_2024_109169 crossref_primary_10_1016_j_patrec_2015_11_006 crossref_primary_10_1109_TEM_2019_2939398 crossref_primary_10_1007_s10044_015_0447_5 crossref_primary_10_1109_ACCESS_2023_3331592 crossref_primary_10_3390_app12010298 crossref_primary_10_1007_s44163_024_00102_x crossref_primary_10_1016_j_dajour_2022_100027 crossref_primary_10_1016_j_eswa_2024_125418 crossref_primary_10_1016_j_autcon_2023_104755 crossref_primary_10_1109_ACCESS_2023_3252374 crossref_primary_10_1016_j_socnet_2019_08_001 crossref_primary_10_1109_TCE_2023_3279836 crossref_primary_10_1016_j_ejor_2021_12_034 crossref_primary_10_1109_TBME_2015_2415733 crossref_primary_10_1016_j_ejor_2017_03_056 crossref_primary_10_1016_j_ejor_2023_07_011 crossref_primary_10_1186_s12859_016_1223_2 crossref_primary_10_1016_j_amc_2023_127904 crossref_primary_10_1016_j_measurement_2025_117209 crossref_primary_10_1002_sta4_70098 crossref_primary_10_1145_3653298 crossref_primary_10_1016_j_comcom_2016_12_020 crossref_primary_10_1007_s00521_012_1101_4 crossref_primary_10_1016_j_engappai_2024_109249 crossref_primary_10_1016_j_physrep_2013_08_002 crossref_primary_10_1007_s41870_022_01028_2 crossref_primary_10_1016_j_ejor_2013_04_027 crossref_primary_10_1186_s13673_017_0103_8 crossref_primary_10_3390_app131810362 crossref_primary_10_1109_TSIPN_2023_3276687 crossref_primary_10_32604_cmes_2023_026083 crossref_primary_10_2118_212833_PA crossref_primary_10_1109_TCYB_2025_3526176 crossref_primary_10_1109_ACCESS_2025_3600986 crossref_primary_10_1111_itor_13062 crossref_primary_10_1016_j_eswa_2021_115108 crossref_primary_10_1002_qute_201900029 crossref_primary_10_2333_bhmk_40_85 crossref_primary_10_1002_cmm4_1020 crossref_primary_10_1371_journal_pone_0210236 crossref_primary_10_1016_j_knosys_2018_11_007 crossref_primary_10_1109_JSEN_2020_2981976 crossref_primary_10_1016_j_eswa_2014_03_008 crossref_primary_10_1109_TPAMI_2020_2974475 crossref_primary_10_1109_TKDE_2025_3569681 crossref_primary_10_1038_s41598_022_25411_y crossref_primary_10_1080_21680566_2023_2240961 crossref_primary_10_1109_TMC_2020_2999852 crossref_primary_10_1007_s43441_024_00705_7 crossref_primary_10_1016_j_jmsy_2025_04_011 crossref_primary_10_1016_j_engappai_2024_108215 crossref_primary_10_3389_fncir_2021_662882 crossref_primary_10_1007_s10586_021_03430_0 crossref_primary_10_1109_LGRS_2024_3407949 crossref_primary_10_7717_peerj_cs_1621 crossref_primary_10_1007_s10844_024_00897_2 crossref_primary_10_1002_gepi_22164 crossref_primary_10_1007_s00521_014_1628_7 crossref_primary_10_1111_jace_20128 crossref_primary_10_1007_s10044_025_01432_x crossref_primary_10_1109_ACCESS_2019_2929948 crossref_primary_10_1007_s11760_019_01419_2 crossref_primary_10_1007_s10878_020_00574_4 crossref_primary_10_1016_j_eswa_2022_119099 crossref_primary_10_1007_s12293_022_00365_w crossref_primary_10_1109_LSP_2020_3023587 crossref_primary_10_1109_ACCESS_2025_3553056 crossref_primary_10_1016_j_aca_2019_10_071 crossref_primary_10_1155_2024_5555191 crossref_primary_10_1111_mice_13466 crossref_primary_10_1007_s00521_017_3036_2 crossref_primary_10_1016_j_laa_2011_11_032 crossref_primary_10_1007_s10586_017_1472_5 crossref_primary_10_1016_j_patcog_2012_01_005 crossref_primary_10_1155_2015_170138 crossref_primary_10_1049_iet_cvi_2014_0131 crossref_primary_10_1080_10106049_2024_2326008 crossref_primary_10_1155_2022_8153249 crossref_primary_10_1007_s10479_024_05868_y crossref_primary_10_1007_s11042_023_17909_y crossref_primary_10_1007_s44336_024_00008_3 crossref_primary_10_1016_j_cam_2020_112795 crossref_primary_10_1109_TSG_2016_2602480 crossref_primary_10_1016_j_eswa_2021_116475 crossref_primary_10_1186_s12938_016_0154_5 crossref_primary_10_1016_j_dam_2021_02_040 crossref_primary_10_1016_j_eswa_2015_07_074 crossref_primary_10_1016_j_jmsy_2016_09_007 crossref_primary_10_1155_cplx_6950334 crossref_primary_10_1016_j_eswa_2015_05_009 crossref_primary_10_1016_j_ijpe_2021_108272 crossref_primary_10_1109_TNNLS_2023_3243914 crossref_primary_10_1371_journal_pone_0304716 crossref_primary_10_1016_j_ejor_2011_10_013 crossref_primary_10_1007_s00521_013_1439_2 crossref_primary_10_1007_s41060_017_0069_7 crossref_primary_10_1371_journal_pone_0169355 crossref_primary_10_1111_risa_13795 |
| Cites_doi | 10.1109/34.868688 10.1086/170483 10.1109/SFCS.1988.21958 10.1007/s00265-003-0651-y 10.1145/196244.196603 10.1109/34.244673 10.1103/PhysRevE.74.036104 10.1186/1471-2105-8-250 10.1007/978-3-540-30115-8_35 10.1007/BF02614317 10.1007/s11222-007-9033-z 10.1016/j.physrep.2005.10.009 10.1214/009053607000000640 10.1109/ICCV.2003.1238361 10.1016/S0166-218X(98)00083-3 10.1002/prot.20147 10.1109/TPAMI.2004.1262185 10.1103/PhysRevE.69.026113 10.1287/mnsc.17.3.219 10.2307/2344237 10.1109/43.159993 10.1186/1471-2105-6-260 10.1109/SUPERC.1990.129995 10.1109/43.310898 10.21136/CMJ.1975.101357 10.1006/jmbi.1999.3058 10.1016/j.patcog.2007.05.018 10.1142/S0219525903001067 10.1016/j.patcog.2006.05.021 10.1086/jar.33.4.3629752 10.1147/rd.175.0420 10.1016/S0031-3203(03)00084-0 10.1109/ICDM.2001.989507 10.1016/j.cosrev.2007.05.001 |
| ContentType | Journal Article |
| Copyright | 2010 Elsevier B.V. 2015 INIST-CNRS Copyright Elsevier Sequoia S.A. Jun 1, 2011 |
| Copyright_xml | – notice: 2010 Elsevier B.V. – notice: 2015 INIST-CNRS – notice: Copyright Elsevier Sequoia S.A. Jun 1, 2011 |
| DBID | AAYXX CITATION OQ6 IQODW DKI X2L 7SC 7TB 8FD FR3 JQ2 L7M L~C L~D 7TA JG9 |
| DOI | 10.1016/j.ejor.2010.08.012 |
| DatabaseName | CrossRef ECONIS Pascal-Francis RePEc IDEAS RePEc Computer and Information Systems Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database Engineering Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Materials Business File Materials Research Database |
| DatabaseTitle | CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional Materials Research Database Materials Business File |
| DatabaseTitleList | Technology Research Database Materials Research Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Computer Science Business Applied Sciences |
| EISSN | 1872-6860 |
| EndPage | 231 |
| ExternalDocumentID | 2270514311 eeeejores_v_3a211_3ay_3a2011_3ai_3a2_3ap_3a221_231_htm 23897471 654683395 10_1016_j_ejor_2010_08_012 S0377221710005497 |
| Genre | Feature |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 1B1 1OL 1RT 1~. 1~5 29G 4.4 41~ 457 4G. 5GY 5VS 6OB 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AAXUO AAYFN AAYOK ABAOU ABBOA ABFNM ABFRF ABJNI ABMAC ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFO ACGFS ACIWK ACNCT ACNNM ACRLP ACZNC ADBBV ADEZE ADGUI ADIYS ADJOM ADMUD AEBSH AEFWE AEKER AENEX AFFNX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHZHX AI. AIALX AIEXJ AIGVJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR ASPBG AVWKF AXJTR AZFZN BKOJK BKOMP BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HAMUX HVGLF HZ~ IHE J1W KOM LY1 M41 MHUIS MO0 MS~ N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 R2- RIG ROL RPZ RXW SCC SDF SDG SDP SDS SES SEW SPC SPCBC SSB SSD SSV SSW SSZ T5K TAE TN5 U5U VH1 WUQ XPP ZMT ~02 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO ADXHL AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD OQ6 AFXIZ AGCQF AGRNS BNPGV IQODW SSH 02 08R 0R 1 41 6XO 8P AAPBV ABFLS ADALY DKI G- HZ IPNFZ K M MS PQEST STF X X2L 7SC 7TB 8FD FR3 JQ2 L7M L~C L~D 7TA JG9 |
| ID | FETCH-LOGICAL-c623t-b3b9c54c35a27ca3a3f2105e7333d97c40e796aefae2e7670da29bb8ae0f1e2c3 |
| ISICitedReferencesCount | 162 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000288308800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0377-2217 |
| IngestDate | Wed Oct 01 14:28:15 EDT 2025 Sun Nov 09 08:14:53 EST 2025 Wed Aug 18 03:50:56 EDT 2021 Mon Jul 21 09:13:46 EDT 2025 Sat Mar 08 16:11:55 EST 2025 Sat Nov 29 07:22:30 EST 2025 Tue Nov 18 22:35:30 EST 2025 Fri Feb 23 02:32:29 EST 2024 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 2 |
| Keywords | Spectral clustering Ratio cut Modularity Min-cut ncut Cluster analysis Spectral method Modular system Graph theory Data mining Weighted graph Laplacian Graph decomposition Graph cut Classification Graph method |
| Language | English |
| License | CC BY 4.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c623t-b3b9c54c35a27ca3a3f2105e7333d97c40e796aefae2e7670da29bb8ae0f1e2c3 |
| Notes | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
| OpenAccessLink | http://doi.org/10.1016/j.ejor.2010.08.012 |
| PQID | 852656211 |
| PQPubID | 45678 |
| PageCount | 11 |
| ParticipantIDs | proquest_miscellaneous_1019691541 proquest_journals_852656211 repec_primary_eeeejores_v_3a211_3ay_3a2011_3ai_3a2_3ap_3a221_231_htm pascalfrancis_primary_23897471 econis_primary_654683395 crossref_citationtrail_10_1016_j_ejor_2010_08_012 crossref_primary_10_1016_j_ejor_2010_08_012 elsevier_sciencedirect_doi_10_1016_j_ejor_2010_08_012 |
| PublicationCentury | 2000 |
| PublicationDate | 2011-06-01 |
| PublicationDateYYYYMMDD | 2011-06-01 |
| PublicationDate_xml | – month: 06 year: 2011 text: 2011-06-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | Amsterdam |
| PublicationPlace_xml | – name: Amsterdam |
| PublicationSeriesTitle | European Journal of Operational Research |
| PublicationTitle | European journal of operational research |
| PublicationYear | 2011 |
| Publisher | Elsevier B.V Elsevier Elsevier Sequoia S.A |
| Publisher_xml | – name: Elsevier B.V – name: Elsevier – name: Elsevier Sequoia S.A |
| References | Cvetković, Doob, Sachs (b0050) 1979 Singh, Mukherjee, Peng, Xu (b0235) 2008; vol. 20 Meilă, M., Xu, L., 2004. Multiway Cuts and Spectral Clustering, Technical Report. 442, University of Washington. Anderson, E., Bai, Z., Bischof, C., Demmel, J., Dongarra, J., Croz, J.D., Greenbaum, A., Hammarling, S., Mckenney, A., Sorensen, D., 1990. LAPACK: A Portable Linear Algebra Library for High-Performance Computers, Technical Report CS-90-105, Computer Science Department, University of Tennessee, Knoxville, TN. Chan, Schlag, Zien (b0035) 1994; 13 Stewart, Sun (b0240) 1990 Hagen, Kahng (b0120) 1992; 11 Schrijver (b0220) 2003; vol. B Ding, He, Meraz, Holbrook (b0070) 2004; 57 Zha, H., Ding, C., Gu, M., He, X., Simon, H., 2002. Spectral relaxation for Kim, Choi (b0150) 2006; 39 Alpert, Kahng, Yao (b0010) 1999; 90 Luo, Wilson, Hancock (b0165) 2003; 36 Ushioda, A., Kawasaki, J., 1996. Hierarchical clustering of words and application to nlp tasks. In: Ejerhed, E., Dagan, I. (Eds.), Fourth Workshop on Very Large Corpora. Association for Computational Linguistics, Somerset, New Jersey. pp. 28–41. Gu, M., Zha, H., Ding, C., He, X., Simon, H., 2001. Spectral Relaxation Models and Structure Analysis for Venables, W.N., Smith, D.M., 2010. An Introduction to R. R Development Core Team, The R Foundation for Statistical Computing, version 2.11.1. Meilă, M., Shi, J., 2001. A random walks view of spectral segmentation. In: Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics. Zachary (b0290) 1977; 33 Kannan, Vishveshwara (b0145) 1999; 292 Leighton, T., Rao, S., 1988. An approximate max-flow min-cut theorem for uniform multicommodity flow problems with applications to approximation algorithms. In: Annual IEEE Symposium on Foundations of Computer Science, pp. 422–431. Xing, E., Jordan, M., 2003. On semidefinite relaxation for normalized Hall (b0125) 1970; 17 way Graph Clustering and Bi-clustering, Technical Report. CSE-01-007, The Pennsylvania State University. Kulis, B., Surendran, A.C., Platt, J.C., 2007. Fast low-rank semidefinite programming for embedding and clustering. In: Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics. Gleiser, Danon (b0110) 2003; 6 Lusseau, Schneider, Boisseau, Haase, Slooten, Dawson (b0170) 2003; 54 Von Luxburg (b0255) 2007; 17 Hansen, Jaumard (b0130) 1997; 79 Newman (b0195) 2006; 74 Huttenhower, Flamholz, Landis, Sahi, Myers, Olszewski, Hibbs, Siemers, Troyanskaya, Coller (b0140) 2007; 8 Ding, C., He, X., Zha, H., Gu, M., Simon, H., 2001. A min–max cut algorithm for graph partitioning and data clustering. In: Proceedings of the IEEE International Conference on Data Mining, ICDM 2001, pp. 107–114. Ford, Fulkerson (b0095) 1962 Maier, M., von Luxburg, U., Hein, M., 2009. Influence of graph construction on graph-based clustering measures. In: Koller, D., Schuurmans, D., Bengio, Y., Bottou, L., Curran, Hook, R. (Eds.), Advances in Neural Information Processing Systems, vol. 21, pp. 1025–1032. Zelnik-Manor, Perona (b0295) 2004; vol. 17 Forman, Clemons, Schreiber, Haggarty (b0100) 2005; 6 Shi, Malik (b0230) 2000; 22 Hückel (b0135) 1931; 72 Donath, Hoffman (b0080) 1973; 17 means clustering. In: Advances in Neural Information Processing Systems, vol. 14. pp. 1057–1064. Filippone, Camastra, Masulli, Rovetta (b0090) 2008; 41 Alpert, C.J., Kahng, A.B., 1994. Multi-way partitioning via spacefilling curves and dynamic programming. In: Proceeding of the 31st ACM/IEEE Design Automation Conference, pp. 652–657. Newman, Girvan (b0200) 2004; 69 Von Luxburg, Belkin, Bousquet (b0260) 2008; 36 De Bie, Cristianini (b0055) 2006; 7 Saerens, M., Fouss, F., Yen, L., Dupont, P., 2004. The principal components analysis of a graph, and its relationships to spectral clustering. In: Machine Learning: ECML 2004, Lecture Notes in Computer Science, vol. 3201, pp. 371–383. Mohar (b0190) 1991; 2 Bach, Jordan (b0020) 2004; vol. 16 Wu, Leahy (b0275) 1993; 15 Ding, He, Simon (b0075) 2005 Cormack (b0045) 1971; 134 Schaeffer (b0215) 2007; 1 Diestel (b0060) 2005; vol. 173 Chung (b0040) 1994 Boccaletti, Latora, Moreno, Chavez, Hwang (b0025) 2006; 424 Brand, M., Huang, K., 2003. A unifying theorem for spectral embedding and clustering. In: Bishop, C., Frey, B. (Eds.), Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics. Fiedler (b0085) 1975; 25 White, Frenk (b0270) 1991; 379 Yu, S.X., Shi, J., 2003. Multiclass spectral clustering. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, pp. 313–319. cut and connections to spectral clustering, Technical Report. CSD-03-1265, University of California, Berkeley. Wei, Y. C., Cheng, C. K., 1989. Towards efficient hierarchical designs by ratio cut partitioning. In: Proceedings of the IEEE International Conference on Computer-Aided Design. pp. 298–301. Fowlkes, Belongie, Chung, Malik (b0105) 2004; 26 Ng, Jordan, Weiss (b0205) 2002; vol. 14 Shi, J., Malik, J., 1997. Normalized cuts and image segmentation. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 731–737. 10.1016/j.ejor.2010.08.012_b0185 Diestel (10.1016/j.ejor.2010.08.012_b0060) 2005; vol. 173 Hagen (10.1016/j.ejor.2010.08.012_b0120) 1992; 11 Schrijver (10.1016/j.ejor.2010.08.012_b0220) 2003; vol. B 10.1016/j.ejor.2010.08.012_b0180 Ng (10.1016/j.ejor.2010.08.012_b0205) 2002; vol. 14 10.1016/j.ejor.2010.08.012_b0300 10.1016/j.ejor.2010.08.012_b0225 10.1016/j.ejor.2010.08.012_b0065 Fowlkes (10.1016/j.ejor.2010.08.012_b0105) 2004; 26 Lusseau (10.1016/j.ejor.2010.08.012_b0170) 2003; 54 10.1016/j.ejor.2010.08.012_b0265 Fiedler (10.1016/j.ejor.2010.08.012_b0085) 1975; 25 Huttenhower (10.1016/j.ejor.2010.08.012_b0140) 2007; 8 Von Luxburg (10.1016/j.ejor.2010.08.012_b0255) 2007; 17 Cvetković (10.1016/j.ejor.2010.08.012_b0050) 1979 Kannan (10.1016/j.ejor.2010.08.012_b0145) 1999; 292 Donath (10.1016/j.ejor.2010.08.012_b0080) 1973; 17 Kim (10.1016/j.ejor.2010.08.012_b0150) 2006; 39 10.1016/j.ejor.2010.08.012_b0250 Gleiser (10.1016/j.ejor.2010.08.012_b0110) 2003; 6 10.1016/j.ejor.2010.08.012_b0015 10.1016/j.ejor.2010.08.012_b0175 Filippone (10.1016/j.ejor.2010.08.012_b0090) 2008; 41 10.1016/j.ejor.2010.08.012_b0210 Alpert (10.1016/j.ejor.2010.08.012_b0010) 1999; 90 Singh (10.1016/j.ejor.2010.08.012_b0235) 2008; vol. 20 Mohar (10.1016/j.ejor.2010.08.012_b0190) 1991; 2 Zachary (10.1016/j.ejor.2010.08.012_b0290) 1977; 33 Zelnik-Manor (10.1016/j.ejor.2010.08.012_b0295) 2004; vol. 17 10.1016/j.ejor.2010.08.012_b0160 Schaeffer (10.1016/j.ejor.2010.08.012_b0215) 2007; 1 Hückel (10.1016/j.ejor.2010.08.012_b0135) 1931; 72 10.1016/j.ejor.2010.08.012_b0280 10.1016/j.ejor.2010.08.012_b0245 Hall (10.1016/j.ejor.2010.08.012_b0125) 1970; 17 10.1016/j.ejor.2010.08.012_b0005 Newman (10.1016/j.ejor.2010.08.012_b0195) 2006; 74 10.1016/j.ejor.2010.08.012_b0285 Ding (10.1016/j.ejor.2010.08.012_b0070) 2004; 57 Bach (10.1016/j.ejor.2010.08.012_b0020) 2004; vol. 16 Cormack (10.1016/j.ejor.2010.08.012_b0045) 1971; 134 Newman (10.1016/j.ejor.2010.08.012_b0200) 2004; 69 Hansen (10.1016/j.ejor.2010.08.012_b0130) 1997; 79 White (10.1016/j.ejor.2010.08.012_b0270) 1991; 379 Chung (10.1016/j.ejor.2010.08.012_b0040) 1994 Shi (10.1016/j.ejor.2010.08.012_b0230) 2000; 22 Luo (10.1016/j.ejor.2010.08.012_b0165) 2003; 36 10.1016/j.ejor.2010.08.012_b0030 De Bie (10.1016/j.ejor.2010.08.012_b0055) 2006; 7 Ford (10.1016/j.ejor.2010.08.012_b0095) 1962 Boccaletti (10.1016/j.ejor.2010.08.012_b0025) 2006; 424 Chan (10.1016/j.ejor.2010.08.012_b0035) 1994; 13 Ding (10.1016/j.ejor.2010.08.012_b0075) 2005 10.1016/j.ejor.2010.08.012_b0115 Wu (10.1016/j.ejor.2010.08.012_b0275) 1993; 15 10.1016/j.ejor.2010.08.012_b0155 Forman (10.1016/j.ejor.2010.08.012_b0100) 2005; 6 Stewart (10.1016/j.ejor.2010.08.012_b0240) 1990 Von Luxburg (10.1016/j.ejor.2010.08.012_b0260) 2008; 36 |
| References_xml | – reference: Meilă, M., Shi, J., 2001. A random walks view of spectral segmentation. In: Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics. – start-page: 530 year: 2005 end-page: 538 ident: b0075 article-title: Nonnegative Lagrangian relaxation of publication-title: Machine Learning: ECML 2005 – reference: Shi, J., Malik, J., 1997. Normalized cuts and image segmentation. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 731–737. – volume: 13 start-page: 1088 year: 1994 end-page: 1096 ident: b0035 article-title: Spectral k-way ratio-cut partitioning and clustering publication-title: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems – volume: 7 start-page: 1409 year: 2006 end-page: 1436 ident: b0055 article-title: Fast SDP relaxations of graph cut clustering, transduction, and other combinatorial problems publication-title: Journal of Machine Learning Research – reference: Yu, S.X., Shi, J., 2003. Multiclass spectral clustering. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, pp. 313–319. – volume: 17 start-page: 420 year: 1973 end-page: 425 ident: b0080 article-title: Lower bounds for the partitioning of graphs publication-title: IBM Journal Research and Development – reference: Venables, W.N., Smith, D.M., 2010. An Introduction to R. R Development Core Team, The R Foundation for Statistical Computing, version 2.11.1. – reference: Gu, M., Zha, H., Ding, C., He, X., Simon, H., 2001. Spectral Relaxation Models and Structure Analysis for – volume: 2 start-page: 871 year: 1991 end-page: 898 ident: b0190 article-title: The Laplacian spectrum of graphs publication-title: Graph Theory, Combinatorics, and Applications – volume: 25 start-page: 619 year: 1975 end-page: 633 ident: b0085 article-title: A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory publication-title: Czechoslovak Mathematical Journal – reference: Ushioda, A., Kawasaki, J., 1996. Hierarchical clustering of words and application to nlp tasks. In: Ejerhed, E., Dagan, I. (Eds.), Fourth Workshop on Very Large Corpora. Association for Computational Linguistics, Somerset, New Jersey. pp. 28–41. – reference: -means clustering. In: Advances in Neural Information Processing Systems, vol. 14. pp. 1057–1064. – volume: vol. 20 start-page: 1353 year: 2008 end-page: 1360 ident: b0235 article-title: Ensemble clustering using semidefinite programming publication-title: Advances in Neural Information Processing Systems – volume: 6 start-page: 565 year: 2003 end-page: 573 ident: b0110 article-title: Community structure in jazz publication-title: Advances in Complex Systems – reference: Ding, C., He, X., Zha, H., Gu, M., Simon, H., 2001. A min–max cut algorithm for graph partitioning and data clustering. In: Proceedings of the IEEE International Conference on Data Mining, ICDM 2001, pp. 107–114. – reference: Alpert, C.J., Kahng, A.B., 1994. Multi-way partitioning via spacefilling curves and dynamic programming. In: Proceeding of the 31st ACM/IEEE Design Automation Conference, pp. 652–657. – volume: 26 start-page: 214 year: 2004 end-page: 225 ident: b0105 article-title: Spectral grouping using the Nyström method publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – reference: Maier, M., von Luxburg, U., Hein, M., 2009. Influence of graph construction on graph-based clustering measures. In: Koller, D., Schuurmans, D., Bengio, Y., Bottou, L., Curran, Hook, R. (Eds.), Advances in Neural Information Processing Systems, vol. 21, pp. 1025–1032. – reference: Zha, H., Ding, C., Gu, M., He, X., Simon, H., 2002. Spectral relaxation for – volume: 72 start-page: 310 year: 1931 end-page: 337 ident: b0135 article-title: Quantentheoretische Beiträge zum Benzolproblem publication-title: Zeitschrift füur Physik a Hadrons and Nuclei – reference: Brand, M., Huang, K., 2003. A unifying theorem for spectral embedding and clustering. In: Bishop, C., Frey, B. (Eds.), Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics. – volume: 8 start-page: 250 year: 2007 ident: b0140 article-title: Nearest neighbor networks: Clustering expression data based on gene neighborhoods publication-title: BMC Bioinformatics – volume: 57 start-page: 99 year: 2004 end-page: 108 ident: b0070 article-title: A unified representation of multiprotein complex data for modeling interaction networks publication-title: Proteins: Structure, Function, and Bioinformatics – volume: 36 start-page: 2213 year: 2003 end-page: 2230 ident: b0165 article-title: Spectral embedding of graphs publication-title: Pattern Recognition – volume: 292 start-page: 441 year: 1999 end-page: 464 ident: b0145 article-title: Identification of side-chain clusters in protein structures by a graph spectral method publication-title: Journal of Molecular Biology – year: 1962 ident: b0095 article-title: Flows in Networks – volume: 134 start-page: 321 year: 1971 end-page: 367 ident: b0045 article-title: A review of classification publication-title: Journal of the Royal Statistical Society – year: 1979 ident: b0050 article-title: Spectra of Graphs: Theory and Application – volume: 17 start-page: 219 year: 1970 end-page: 229 ident: b0125 article-title: An r-dimensional quadratic placement algorithm publication-title: Management Science – volume: 6 start-page: 260 year: 2005 ident: b0100 article-title: SpectralNET – An application for spectral graph analysis and visualization publication-title: BMC Bioinformatics – volume: 22 start-page: 888 year: 2000 end-page: 905 ident: b0230 article-title: Normalized cuts and image segmentation publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – volume: vol. B year: 2003 ident: b0220 article-title: Combinatorial Optimization publication-title: Polyhedra and Efficiency – volume: 33 start-page: 452 year: 1977 end-page: 473 ident: b0290 article-title: An information flow model for conflict and fission in small groups publication-title: Journal of Anthropological Research – year: 1990 ident: b0240 article-title: Matrix Perturbation Theory publication-title: Computer Science and Scientific Computing – volume: 69 start-page: 026113 year: 2004 ident: b0200 article-title: Finding and evaluating community structure in networks publication-title: Physical Review E – reference: Meilă, M., Xu, L., 2004. Multiway Cuts and Spectral Clustering, Technical Report. 442, University of Washington. – volume: 74 start-page: 036 year: 2006 end-page: 104 ident: b0195 article-title: Finding community structure in networks using the eigenvectors of matrices publication-title: Physical Review E – volume: 41 start-page: 176 year: 2008 end-page: 190 ident: b0090 article-title: A survey of kernel and spectral methods for clustering publication-title: Pattern Recognition – volume: 11 start-page: 1074 year: 1992 end-page: 1088 ident: b0120 article-title: New spectral methods for ratio cut partitioning and clustering publication-title: IEEE Transactions on Computer-Aided Design – volume: 1 start-page: 27 year: 2007 end-page: 64 ident: b0215 article-title: Graph clustering publication-title: Computer Science Review – reference: Xing, E., Jordan, M., 2003. On semidefinite relaxation for normalized – volume: 54 start-page: 396 year: 2003 end-page: 405 ident: b0170 article-title: The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations publication-title: Behavioral Ecology and Sociobiology – reference: Anderson, E., Bai, Z., Bischof, C., Demmel, J., Dongarra, J., Croz, J.D., Greenbaum, A., Hammarling, S., Mckenney, A., Sorensen, D., 1990. LAPACK: A Portable Linear Algebra Library for High-Performance Computers, Technical Report CS-90-105, Computer Science Department, University of Tennessee, Knoxville, TN. – reference: Wei, Y. C., Cheng, C. K., 1989. Towards efficient hierarchical designs by ratio cut partitioning. In: Proceedings of the IEEE International Conference on Computer-Aided Design. pp. 298–301. – volume: 79 start-page: 191 year: 1997 end-page: 215 ident: b0130 article-title: Cluster analysis and mathematical programming publication-title: Mathematical Programming – reference: Saerens, M., Fouss, F., Yen, L., Dupont, P., 2004. The principal components analysis of a graph, and its relationships to spectral clustering. In: Machine Learning: ECML 2004, Lecture Notes in Computer Science, vol. 3201, pp. 371–383. – year: 1994 ident: b0040 article-title: Spectral graph theory publication-title: No. 92 in CBMS Regional Conference Series in Mathematics – volume: 36 start-page: 555 year: 2008 end-page: 586 ident: b0260 article-title: Consistency of spectral clustering publication-title: The Annals of Statistics – reference: Kulis, B., Surendran, A.C., Platt, J.C., 2007. Fast low-rank semidefinite programming for embedding and clustering. In: Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics. – volume: vol. 17 start-page: 1601 year: 2004 end-page: 1608 ident: b0295 article-title: Self-tuning spectral clustering publication-title: Advances in Neural Information Processing Systems – reference: Leighton, T., Rao, S., 1988. An approximate max-flow min-cut theorem for uniform multicommodity flow problems with applications to approximation algorithms. In: Annual IEEE Symposium on Foundations of Computer Science, pp. 422–431. – volume: vol. 173 year: 2005 ident: b0060 article-title: Graph theory publication-title: Graduate Texts in Mathematics – volume: vol. 16 start-page: 305 year: 2004 end-page: 312 ident: b0020 article-title: Learning spectral clustering publication-title: Advances in Neural Information Processing Systems – volume: 379 start-page: 52 year: 1991 end-page: 79 ident: b0270 article-title: Galaxy formation through hierarchical clustering publication-title: Astrophysical Journal – reference: -way Graph Clustering and Bi-clustering, Technical Report. CSE-01-007, The Pennsylvania State University. – reference: -cut and connections to spectral clustering, Technical Report. CSD-03-1265, University of California, Berkeley. – volume: 424 start-page: 175 year: 2006 end-page: 308 ident: b0025 article-title: Complex networks: Structure and dynamics publication-title: Physics Reports – volume: 90 start-page: 3 year: 1999 end-page: 26 ident: b0010 article-title: Spectral partitioning with multiple eigenvectors publication-title: Discrete Applied Mathematics – volume: 15 start-page: 1101 year: 1993 end-page: 1113 ident: b0275 article-title: An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – volume: 39 start-page: 2025 year: 2006 end-page: 2035 ident: b0150 article-title: Semidefinite spectral clustering publication-title: Pattern Recognition – volume: vol. 14 start-page: 849 year: 2002 end-page: 856 ident: b0205 article-title: On spectral clustering: Analysis and an algorithm publication-title: Advances in Neural Information Processing Systems – volume: 17 start-page: 395 year: 2007 end-page: 416 ident: b0255 article-title: A tutorial on spectral clustering publication-title: Statistics and Computing – volume: 72 start-page: 310 year: 1931 ident: 10.1016/j.ejor.2010.08.012_b0135 article-title: Quantentheoretische Beiträge zum Benzolproblem publication-title: Zeitschrift füur Physik a Hadrons and Nuclei – volume: 22 start-page: 888 year: 2000 ident: 10.1016/j.ejor.2010.08.012_b0230 article-title: Normalized cuts and image segmentation publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.868688 – volume: 379 start-page: 52 issue: Part 1 year: 1991 ident: 10.1016/j.ejor.2010.08.012_b0270 article-title: Galaxy formation through hierarchical clustering publication-title: Astrophysical Journal doi: 10.1086/170483 – volume: 7 start-page: 1409 year: 2006 ident: 10.1016/j.ejor.2010.08.012_b0055 article-title: Fast SDP relaxations of graph cut clustering, transduction, and other combinatorial problems publication-title: Journal of Machine Learning Research – ident: 10.1016/j.ejor.2010.08.012_b0160 doi: 10.1109/SFCS.1988.21958 – volume: 54 start-page: 396 year: 2003 ident: 10.1016/j.ejor.2010.08.012_b0170 article-title: The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations publication-title: Behavioral Ecology and Sociobiology doi: 10.1007/s00265-003-0651-y – volume: vol. 17 start-page: 1601 year: 2004 ident: 10.1016/j.ejor.2010.08.012_b0295 article-title: Self-tuning spectral clustering – volume: vol. 173 year: 2005 ident: 10.1016/j.ejor.2010.08.012_b0060 article-title: Graph theory – volume: vol. 20 start-page: 1353 year: 2008 ident: 10.1016/j.ejor.2010.08.012_b0235 article-title: Ensemble clustering using semidefinite programming – ident: 10.1016/j.ejor.2010.08.012_b0115 – ident: 10.1016/j.ejor.2010.08.012_b0005 doi: 10.1145/196244.196603 – volume: vol. 16 start-page: 305 year: 2004 ident: 10.1016/j.ejor.2010.08.012_b0020 article-title: Learning spectral clustering – volume: 15 start-page: 1101 issue: 11 year: 1993 ident: 10.1016/j.ejor.2010.08.012_b0275 article-title: An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.244673 – volume: 74 start-page: 036 year: 2006 ident: 10.1016/j.ejor.2010.08.012_b0195 article-title: Finding community structure in networks using the eigenvectors of matrices publication-title: Physical Review E doi: 10.1103/PhysRevE.74.036104 – ident: 10.1016/j.ejor.2010.08.012_b0300 – ident: 10.1016/j.ejor.2010.08.012_b0265 – volume: 8 start-page: 250 year: 2007 ident: 10.1016/j.ejor.2010.08.012_b0140 article-title: Nearest neighbor networks: Clustering expression data based on gene neighborhoods publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-8-250 – ident: 10.1016/j.ejor.2010.08.012_b0210 doi: 10.1007/978-3-540-30115-8_35 – volume: 79 start-page: 191 year: 1997 ident: 10.1016/j.ejor.2010.08.012_b0130 article-title: Cluster analysis and mathematical programming publication-title: Mathematical Programming doi: 10.1007/BF02614317 – volume: 17 start-page: 395 issue: 4 year: 2007 ident: 10.1016/j.ejor.2010.08.012_b0255 article-title: A tutorial on spectral clustering publication-title: Statistics and Computing doi: 10.1007/s11222-007-9033-z – volume: 424 start-page: 175 year: 2006 ident: 10.1016/j.ejor.2010.08.012_b0025 article-title: Complex networks: Structure and dynamics publication-title: Physics Reports doi: 10.1016/j.physrep.2005.10.009 – volume: 36 start-page: 555 year: 2008 ident: 10.1016/j.ejor.2010.08.012_b0260 article-title: Consistency of spectral clustering publication-title: The Annals of Statistics doi: 10.1214/009053607000000640 – ident: 10.1016/j.ejor.2010.08.012_b0285 doi: 10.1109/ICCV.2003.1238361 – volume: 90 start-page: 3 year: 1999 ident: 10.1016/j.ejor.2010.08.012_b0010 article-title: Spectral partitioning with multiple eigenvectors publication-title: Discrete Applied Mathematics doi: 10.1016/S0166-218X(98)00083-3 – volume: 57 start-page: 99 year: 2004 ident: 10.1016/j.ejor.2010.08.012_b0070 article-title: A unified representation of multiprotein complex data for modeling interaction networks publication-title: Proteins: Structure, Function, and Bioinformatics doi: 10.1002/prot.20147 – volume: 26 start-page: 214 year: 2004 ident: 10.1016/j.ejor.2010.08.012_b0105 article-title: Spectral grouping using the Nyström method publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/TPAMI.2004.1262185 – volume: 69 start-page: 026113 year: 2004 ident: 10.1016/j.ejor.2010.08.012_b0200 article-title: Finding and evaluating community structure in networks publication-title: Physical Review E doi: 10.1103/PhysRevE.69.026113 – year: 1979 ident: 10.1016/j.ejor.2010.08.012_b0050 – volume: 17 start-page: 219 year: 1970 ident: 10.1016/j.ejor.2010.08.012_b0125 article-title: An r-dimensional quadratic placement algorithm publication-title: Management Science doi: 10.1287/mnsc.17.3.219 – volume: 134 start-page: 321 year: 1971 ident: 10.1016/j.ejor.2010.08.012_b0045 article-title: A review of classification publication-title: Journal of the Royal Statistical Society doi: 10.2307/2344237 – volume: 11 start-page: 1074 year: 1992 ident: 10.1016/j.ejor.2010.08.012_b0120 article-title: New spectral methods for ratio cut partitioning and clustering publication-title: IEEE Transactions on Computer-Aided Design doi: 10.1109/43.159993 – volume: vol. B year: 2003 ident: 10.1016/j.ejor.2010.08.012_b0220 article-title: Combinatorial Optimization – volume: 6 start-page: 260 year: 2005 ident: 10.1016/j.ejor.2010.08.012_b0100 article-title: SpectralNET – An application for spectral graph analysis and visualization publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-6-260 – ident: 10.1016/j.ejor.2010.08.012_b0015 doi: 10.1109/SUPERC.1990.129995 – year: 1994 ident: 10.1016/j.ejor.2010.08.012_b0040 article-title: Spectral graph theory – volume: 2 start-page: 871 year: 1991 ident: 10.1016/j.ejor.2010.08.012_b0190 article-title: The Laplacian spectrum of graphs publication-title: Graph Theory, Combinatorics, and Applications – volume: 13 start-page: 1088 year: 1994 ident: 10.1016/j.ejor.2010.08.012_b0035 article-title: Spectral k-way ratio-cut partitioning and clustering publication-title: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems doi: 10.1109/43.310898 – volume: 25 start-page: 619 year: 1975 ident: 10.1016/j.ejor.2010.08.012_b0085 article-title: A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory publication-title: Czechoslovak Mathematical Journal doi: 10.21136/CMJ.1975.101357 – ident: 10.1016/j.ejor.2010.08.012_b0245 – volume: 292 start-page: 441 year: 1999 ident: 10.1016/j.ejor.2010.08.012_b0145 article-title: Identification of side-chain clusters in protein structures by a graph spectral method publication-title: Journal of Molecular Biology doi: 10.1006/jmbi.1999.3058 – volume: 41 start-page: 176 year: 2008 ident: 10.1016/j.ejor.2010.08.012_b0090 article-title: A survey of kernel and spectral methods for clustering publication-title: Pattern Recognition doi: 10.1016/j.patcog.2007.05.018 – volume: 6 start-page: 565 year: 2003 ident: 10.1016/j.ejor.2010.08.012_b0110 article-title: Community structure in jazz publication-title: Advances in Complex Systems doi: 10.1142/S0219525903001067 – ident: 10.1016/j.ejor.2010.08.012_b0180 – ident: 10.1016/j.ejor.2010.08.012_b0250 – ident: 10.1016/j.ejor.2010.08.012_b0155 – volume: 39 start-page: 2025 issue: 11 year: 2006 ident: 10.1016/j.ejor.2010.08.012_b0150 article-title: Semidefinite spectral clustering publication-title: Pattern Recognition doi: 10.1016/j.patcog.2006.05.021 – ident: 10.1016/j.ejor.2010.08.012_b0030 – volume: vol. 14 start-page: 849 year: 2002 ident: 10.1016/j.ejor.2010.08.012_b0205 article-title: On spectral clustering: Analysis and an algorithm – year: 1962 ident: 10.1016/j.ejor.2010.08.012_b0095 – start-page: 530 year: 2005 ident: 10.1016/j.ejor.2010.08.012_b0075 article-title: Nonnegative Lagrangian relaxation of k-means and spectral clustering – ident: 10.1016/j.ejor.2010.08.012_b0185 – ident: 10.1016/j.ejor.2010.08.012_b0280 – volume: 33 start-page: 452 year: 1977 ident: 10.1016/j.ejor.2010.08.012_b0290 article-title: An information flow model for conflict and fission in small groups publication-title: Journal of Anthropological Research doi: 10.1086/jar.33.4.3629752 – year: 1990 ident: 10.1016/j.ejor.2010.08.012_b0240 article-title: Matrix Perturbation Theory – volume: 17 start-page: 420 issue: 5 year: 1973 ident: 10.1016/j.ejor.2010.08.012_b0080 article-title: Lower bounds for the partitioning of graphs publication-title: IBM Journal Research and Development doi: 10.1147/rd.175.0420 – ident: 10.1016/j.ejor.2010.08.012_b0225 – volume: 36 start-page: 2213 year: 2003 ident: 10.1016/j.ejor.2010.08.012_b0165 article-title: Spectral embedding of graphs publication-title: Pattern Recognition doi: 10.1016/S0031-3203(03)00084-0 – ident: 10.1016/j.ejor.2010.08.012_b0175 – ident: 10.1016/j.ejor.2010.08.012_b0065 doi: 10.1109/ICDM.2001.989507 – volume: 1 start-page: 27 year: 2007 ident: 10.1016/j.ejor.2010.08.012_b0215 article-title: Graph clustering publication-title: Computer Science Review doi: 10.1016/j.cosrev.2007.05.001 |
| SSID | ssj0001515 |
| Score | 2.4888122 |
| Snippet | Graph clustering is an area in cluster analysis that looks for groups of related vertices in a graph. Due to its large applicability, several graph clustering... |
| SourceID | proquest repec pascalfrancis econis crossref elsevier |
| SourceType | Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 221 |
| SubjectTerms | Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Cluster analysis Clustering Computer science; control theory; systems Cutting stock problem Data processing. List processing. Character string processing Exact sciences and technology Graph algorithms Graphs Information retrieval. Graph Laplace transforms Mathematical analysis Matrix Memory organisation. Data processing Min-cut Modularity ncut Operational research Partitioning Ratio cut Software Spectra Spectral clustering Spectral clustering Min-cut Ratio cut ncut Modularity Spectral methods Studies Theoretical computing |
| Title | Spectral methods for graph clustering – A survey |
| URI | https://dx.doi.org/10.1016/j.ejor.2010.08.012 http://www.econis.eu/PPNSET?PPN=654683395 http://econpapers.repec.org/article/eeeejores/v_3a211_3ay_3a2011_3ai_3a2_3ap_3a221-231.htm https://www.proquest.com/docview/852656211 https://www.proquest.com/docview/1019691541 |
| Volume | 211 |
| WOSCitedRecordID | wos000288308800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-6860 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001515 issn: 0377-2217 databaseCode: AIEXJ dateStart: 19950105 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtR1db9Mw0IJ2QiDExwCtDKYgwVOUKrGTOH6cyibgYdrDkPpmOamjpSpJlbTT-PfcxU6a8jHBA5XqWq7ruL7z3fl8H4S8T0WcpEoEsNN46IVsgUYAlHlZzjEclsp9ZpJN8IuLZD4Xl9bjumnTCfCyTG5vxfq_ghraANjoOvsP4O4HhQaoA9ChBLBD-VeAx4zyqL6wyaHbeAtuG5fazVZbjIvQcavfKeStcAoNdacmtPGAdnpjBWwTlYqVdfYp2tv2wJ1NdyazM8w5tLquOqNJcyGP9iWrqnEv0VnSXaA3EWDfua5rXdRqqIEIBpZSRi1mefiAcjHOPUqNU2ZHZqklqsXguGuJpvGRtvyXGq7wC2k3WoblVC-r2prkJVPf2mDvh8xGB62EMRHdJ2PKI5GMyPj089n8S8-jUYxr75fsRK07lbH8-_kJeyLLAeopimZPdnm8hoVXq9ykQtk7q4xrDVAfiCxXz8gTe9ZwTg2OPCf3dHlIHnSuDofkaZfSw7EU_pA8GsSnfEE-dLjkWFxyAJecFpecHS69JF_Pz65mnzybV8PLQNjdeClLRRaFGYsU5ZliiuVw8I80Z4wtBM9CX3MRK50rTTWPub9QVKRporSfB5pm7BUZlVWpj4iTqwTkzTgMwiAJQy7UIoPljJimKk38WExI0C2dzGzQecx9spKddeFS4nJLXG6JCVEDOiFu_5u1CblyZ-8jA5G-bw_9CYk6GEkrTxo5UQJO3TnkyR5A-5FBvMXjdzAhxx2Epd2ajUww0UQMWD4h7_pvgVbjBZwqdbVt8HkiFnBogT4fW8Toh9bwgmnoRt5IpmAUKL9jzW-rBVbhvcZPGsBMAnm9-fb6z3_-mDzc7dU3ZLSpt_otOchuNkVTn9j98AMvBMQa |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Spectral+methods+for+graph+clustering&rft.jtitle=European+journal+of+operational+research&rft.au=Nascimento%2C+Mari%C3%A1+C.+V&rft.au=Carvalho%2C+Andr%C3%A9+Carlos+Ponce+de+Leon+Ferreira&rft.date=2011-06-01&rft.pub=Elsevier&rft.issn=0377-2217&rft.volume=211&rft.issue=2&rft.spage=221&rft.epage=231&rft_id=info:doi/10.1016%2Fj.ejor.2010.08.012&rft.externalDocID=654683395 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0377-2217&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0377-2217&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0377-2217&client=summon |