Node Immunization on Large Graphs: Theory and Algorithms
Given a large graph, like a computer communication network, which k nodes should we immunize (or monitor, or remove), to make it as robust as possible against a computer virus attack? This problem, referred to as the node immunization problem, is the core building block in many high-impact applicati...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on knowledge and data engineering Jg. 28; H. 1; S. 113 - 126 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
01.01.2016
|
| Schlagworte: | |
| ISSN: | 1041-4347 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Given a large graph, like a computer communication network, which k nodes should we immunize (or monitor, or remove), to make it as robust as possible against a computer virus attack? This problem, referred to as the node immunization problem, is the core building block in many high-impact applications, ranging from public health, cybersecurity to viral marketing. A central component in node immunization is to find the best k bridges of a given graph. In this setting, we typically want to determine the relative importance of a node (or a set of nodes) within the graph, for example, how valuable (as a bridge) a person or a group of persons is in a social network. First of all, we propose a novel `bridging' score Dλ, inspired by immunology, and we show that its results agree with intuition for several realistic settings. Since the straightforward way to compute Dλ is computationally intractable, we then focus on the computational issues and propose a surprisingly efficient way (O(nk 2 + m)) to estimate it. Experimental results on real graphs show that (1) the proposed `bridging' score gives mining results consistent with intuition; and (2) the proposed fast solution is up to seven orders of magnitude faster than straightforward alternatives. |
|---|---|
| AbstractList | Given a large graph, like a computer communication network, which k nodes should we immunize (or monitor, or remove), to make it as robust as possible against a computer virus attack? This problem, referred to as the node immunization problem, is the core building block in many high-impact applications, ranging from public health, cybersecurity to viral marketing. A central component in node immunization is to find the best k bridges of a given graph. In this setting, we typically want to determine the relative importance of a node (or a set of nodes) within the graph, for example, how valuable (as a bridge) a person or a group of persons is in a social network. First of all, we propose a novel `bridging' score Dλ, inspired by immunology, and we show that its results agree with intuition for several realistic settings. Since the straightforward way to compute Dλ is computationally intractable, we then focus on the computational issues and propose a surprisingly efficient way (O(nk 2 + m)) to estimate it. Experimental results on real graphs show that (1) the proposed `bridging' score gives mining results consistent with intuition; and (2) the proposed fast solution is up to seven orders of magnitude faster than straightforward alternatives. |
| Author | Chen Chen Duen Horng Chau Hanghang Tong Eliassi-Rad, Tina Tsourakakis, Charalampos E. Faloutsos, Christos Prakash, B. Aditya |
| Author_xml | – sequence: 1 surname: Chen Chen fullname: Chen Chen email: cchen211@asu.edu organization: Comput. Sci. Dept., Arizona State Univ., Tempe, AZ, USA – sequence: 2 surname: Hanghang Tong fullname: Hanghang Tong email: hanghang.tong@asu.edu organization: Comput. Sci. Dept., Arizona State Univ., Tempe, AZ, USA – sequence: 3 givenname: B. Aditya surname: Prakash fullname: Prakash, B. Aditya email: badityap@cs.vt.edu organization: Virginia Tech, Blacksburg, VA, USA – sequence: 4 givenname: Charalampos E. surname: Tsourakakis fullname: Tsourakakis, Charalampos E. email: babis@seas.harvard.edu organization: Sch. of Eng. & Appl. Sci., Harvard Univ., Cambridge, MA, USA – sequence: 5 givenname: Tina surname: Eliassi-Rad fullname: Eliassi-Rad, Tina email: tina@eliassi.org organization: Comput. Sci. Dept., Rutgers Univ., Piscataway, NJ, USA – sequence: 6 givenname: Christos surname: Faloutsos fullname: Faloutsos, Christos email: christos@cs.cmu.edu organization: Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA, USA – sequence: 7 surname: Duen Horng Chau fullname: Duen Horng Chau email: polo@gatech.edu organization: Sch. of Comput. Sci. & Eng., Georgia Tech, Atlanta, GA, USA |
| BookMark | eNp9jz1PwzAQhj0UibbwAxBL_kDKnR3HDltVSqmoYClz5DiX1qhJKjsM5deTfoiBAel0t9zz6n1GbNC0DTF2hzBBhOxh_fo0n3BAOeFJKoXSAzZESDBORKKu2SiETwDQSuOQ6be2pGhZ11-N-zada5uon5XxG4oW3uy34TFab6n1h8g0ZTTdbVrvum0dbthVZXaBbi93zD6e5-vZS7x6Xyxn01VseSq7mLhOC5GWWZEBmlSSrrQGKLjslywN5ySICpFBKjM0aJXBzKrKitIKqFCMmTrnWt-G4KnKretORTtv3C5HyI_S-VE6P0rnF-mexD_k3rva-MO_zP2ZcUT0-69Qo0IpfgDnR2Xb |
| CODEN | ITKEEH |
| CitedBy_id | crossref_primary_10_1016_j_ins_2020_01_037 crossref_primary_10_1016_j_ins_2023_119201 crossref_primary_10_1016_j_jestch_2024_101728 crossref_primary_10_1109_TKDE_2021_3071081 crossref_primary_10_26599_IJCS_2022_9100027 crossref_primary_10_1007_s10618_020_00688_7 crossref_primary_10_1109_ACCESS_2019_2962197 crossref_primary_10_1109_TKDE_2019_2934447 crossref_primary_10_1109_TCSS_2021_3059430 crossref_primary_10_1109_TSP_2025_3527755 crossref_primary_10_1016_j_jocs_2023_101972 crossref_primary_10_1016_j_meegid_2025_105768 crossref_primary_10_1109_TKDE_2022_3163672 crossref_primary_10_3390_systems11090458 crossref_primary_10_1145_2903148 crossref_primary_10_1109_ACCESS_2023_3331220 crossref_primary_10_1016_j_knosys_2024_111632 crossref_primary_10_1007_s10955_017_1923_7 crossref_primary_10_32604_cmes_2024_047156 crossref_primary_10_3390_sym13020156 crossref_primary_10_1108_IDD_09_2016_0032 crossref_primary_10_1007_s41109_019_0122_7 crossref_primary_10_1145_3442342 crossref_primary_10_3390_math12162535 crossref_primary_10_1109_ACCESS_2017_2723838 crossref_primary_10_1109_TSMC_2021_3098630 crossref_primary_10_1109_TNSE_2024_3406415 crossref_primary_10_3389_fphy_2021_805584 crossref_primary_10_1007_s41109_018_0061_8 crossref_primary_10_1016_j_endm_2017_11_051 crossref_primary_10_1016_j_jmateco_2021_102486 crossref_primary_10_3390_app11115115 crossref_primary_10_1016_j_physrep_2022_05_003 crossref_primary_10_1080_24725854_2020_1798037 crossref_primary_10_1016_j_physa_2018_05_107 crossref_primary_10_1109_TCSS_2024_3429400 crossref_primary_10_1109_TNSE_2022_3164357 crossref_primary_10_1109_TKDE_2017_2719026 crossref_primary_10_1007_s11432_018_9855_7 |
| Cites_doi | 10.1155/ASP/2006/79412 10.1109/ICDM.2010.118 10.1109/ICDM.2008.130 10.1007/s10115-013-0671-5 10.1103/PhysRevLett.91.247901 10.1145/1379092.1379108 10.1145/502512.502525 10.1109/JSAC.2013.130610 10.1145/1557019.1557047 10.1109/INFCOM.2005.1498374 10.1109/ICDM.2012.136 10.1145/2339530.2339537 10.1103/PhysRevE.77.016107 10.2307/3033543 10.1109/RELDIS.2003.1238052 10.1137/S0036144500371907 10.1145/2339530.2339601 10.1145/2661829.2662088 10.1017/CBO9780511721649 10.1145/2124295.2124381 10.1145/1081870.1081944 10.1145/2396761.2396795 10.1137/1.9781611972832.43 10.1145/1281192.1281239 10.1007/978-3-642-21916-0_18 10.1016/B978-012088469-8/50050-4 10.1137/1.9781611973440.37 10.1007/s10115-012-0520-y 10.1145/2020408.2020512 10.1016/S1389-1286(00)00083-9 10.1145/1150402.1150412 10.1145/1401890.1401934 10.21136/CMJ.1973.101168 10.1145/2020408.2020431 10.1038/43601 10.1145/948187.948200 10.1145/324133.324140 10.1145/1963405.1963508 10.1145/956750.956769 10.1109/ICDM.2006.149 10.1016/j.socnet.2004.11.009 10.1145/2331042.2331059 10.1109/JSAC.2013.130607 10.1086/jar.33.4.3629752 10.1145/1284680.1284681 10.1109/ICDM.2011.132 |
| ContentType | Journal Article |
| DBID | 97E RIA RIE AAYXX CITATION |
| DOI | 10.1109/TKDE.2015.2465378 |
| DatabaseName | IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Computer Science |
| EndPage | 126 |
| ExternalDocumentID | 10_1109_TKDE_2015_2465378 7181715 |
| Genre | orig-research |
| GroupedDBID | -~X .DC 0R~ 29I 4.4 5GY 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACIWK AENEX AGQYO AGSQL AHBIQ AKQYR ALMA_UNASSIGNED_HOLDINGS ASUFR ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD F5P HZ~ IEDLZ IFIPE IPLJI JAVBF LAI M43 MS~ O9- OCL P2P PQQKQ RIA RIE RNS RXW TAE TN5 UHB AAYXX CITATION |
| ID | FETCH-LOGICAL-c265t-e286b36d9b901a65e8f8800b2500b5da22e3eeb3906591a1c7a19c7fc3dc30f13 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 70 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000366833100010&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1041-4347 |
| IngestDate | Tue Nov 18 22:18:25 EST 2025 Sat Nov 29 04:46:38 EST 2025 Wed Aug 27 02:52:16 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | graph mining Immunization scalability |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c265t-e286b36d9b901a65e8f8800b2500b5da22e3eeb3906591a1c7a19c7fc3dc30f13 |
| PageCount | 14 |
| ParticipantIDs | crossref_primary_10_1109_TKDE_2015_2465378 crossref_citationtrail_10_1109_TKDE_2015_2465378 ieee_primary_7181715 |
| PublicationCentury | 2000 |
| PublicationDate | 2016-Jan.-1 2016-1-1 |
| PublicationDateYYYYMMDD | 2016-01-01 |
| PublicationDate_xml | – month: 01 year: 2016 text: 2016-Jan.-1 day: 01 |
| PublicationDecade | 2010 |
| PublicationTitle | IEEE transactions on knowledge and data engineering |
| PublicationTitleAbbrev | TKDE |
| PublicationYear | 2016 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| References | ref57 ref13 ref56 ref12 prakash (ref45) 0 hethcote (ref24) 2000; 42 ref15 ref52 ref11 ref10 ref17 ref16 ref19 valler (ref59) 2012 ref18 ref51 karypis (ref27) 0 zha (ref66) 0 ng (ref40) 0 tong (ref55) 2006 ref46 ref48 ref47 ref42 stewart (ref53) 1990 ref44 tuli (ref58) 0 maiya (ref33) 2011 ref49 ref8 ref7 ref9 ref4 ref6 ref5 moody (ref36) 0 habiba (ref21) 0 habiba (ref22) 2013 fiedler (ref14) 1973; 23 ref35 ref34 ref31 sun (ref54) 0 ref32 nguyen (ref41) 2013 ref2 ref39 ref38 yamagishi (ref64) 2011; 20 berger-wolf (ref3) 0 shi (ref50) 0 munro (ref37) 0 ref67 ref23 ref26 ref25 ref20 ref65 xin (ref63) 0 ref28 ref29 krause (ref30) 0 albert (ref1) 1999; 401 ref60 ref62 ref61 page (ref43) 1998 |
| References_xml | – year: 2013 ident: ref22 article-title: Critical individuals in dynamic population networks – ident: ref56 doi: 10.1155/ASP/2006/79412 – ident: ref10 doi: 10.1109/ICDM.2010.118 – ident: ref12 doi: 10.1109/ICDM.2008.130 – year: 0 ident: ref21 article-title: Graph theoretic measures for identifying effective blockers of spreading processes in dynamic networks publication-title: Proc MLG-ICML Workshop Mach Learn Graphs – ident: ref48 doi: 10.1007/s10115-013-0671-5 – ident: ref11 doi: 10.1103/PhysRevLett.91.247901 – ident: ref51 doi: 10.1145/1379092.1379108 – ident: ref13 doi: 10.1145/502512.502525 – ident: ref42 doi: 10.1109/JSAC.2013.130610 – ident: ref9 doi: 10.1145/1557019.1557047 – ident: ref16 doi: 10.1109/INFCOM.2005.1498374 – ident: ref47 doi: 10.1109/ICDM.2012.136 – ident: ref35 doi: 10.1145/2339530.2339537 – ident: ref38 doi: 10.1103/PhysRevE.77.016107 – ident: ref15 doi: 10.2307/3033543 – ident: ref61 doi: 10.1109/RELDIS.2003.1238052 – year: 1990 ident: ref53 publication-title: Matrix Perturbation Theory – volume: 42 start-page: 599 year: 2000 ident: ref24 article-title: The mathematics of infectious diseases publication-title: SIAM Rev doi: 10.1137/S0036144500371907 – start-page: 849 year: 0 ident: ref40 article-title: On spectral clustering: Analysis and an algorithm publication-title: Proc Adv Neural Inf Process Syst – ident: ref4 doi: 10.1145/2339530.2339601 – start-page: 1057 year: 0 ident: ref66 article-title: Spectral relaxation for k-means clustering publication-title: Proc Adv Neural Inf Process Syst – ident: ref67 doi: 10.1145/2661829.2662088 – ident: ref20 doi: 10.1017/CBO9780511721649 – year: 0 ident: ref45 article-title: Fractional immunization in hospital-transfer graphs – year: 2011 ident: ref33 article-title: Sampling and inference in complex networks – ident: ref52 doi: 10.1145/2124295.2124381 – ident: ref26 doi: 10.1145/1081870.1081944 – ident: ref57 doi: 10.1145/2396761.2396795 – ident: ref18 doi: 10.1137/1.9781611972832.43 – year: 1998 ident: ref43 article-title: The PageRank citation ranking: Bringing order to the web – year: 0 ident: ref37 article-title: Better approximation of betweenness centrality publication-title: Proc 10th Workshop Algorithm Eng Experiments – start-page: 731 year: 0 ident: ref50 article-title: Normalized cuts and image segmentation publication-title: Proc IEEE Conf Comput Vis Pattern Recog – ident: ref31 doi: 10.1145/1281192.1281239 – ident: ref49 doi: 10.1007/978-3-642-21916-0_18 – ident: ref17 doi: 10.1016/B978-012088469-8/50050-4 – volume: 20 start-page: 263 year: 2011 ident: ref64 article-title: Learning attribute-weighted voter model over social networks publication-title: J Mach Learn Res -Proc Track – ident: ref8 doi: 10.1137/1.9781611973440.37 – year: 0 ident: ref58 article-title: Blocking complex contagions using community structure publication-title: Proc Workshop Multiagent Interaction Netw – ident: ref46 doi: 10.1007/s10115-012-0520-y – ident: ref23 doi: 10.1145/2020408.2020512 – ident: ref6 doi: 10.1016/S1389-1286(00)00083-9 – ident: ref2 doi: 10.1145/1150402.1150412 – ident: ref25 doi: 10.1145/1401890.1401934 – volume: 23 start-page: 298 year: 1973 ident: ref14 article-title: Algebraic connectivity of graphs publication-title: Czechoslovak Math J doi: 10.21136/CMJ.1973.101168 – ident: ref34 doi: 10.1145/2020408.2020431 – start-page: 613 year: 2006 ident: ref55 article-title: Fast random walk with restart and its applications publication-title: Proc Int Conf Data Mining – start-page: 933 year: 0 ident: ref3 article-title: Working for influence: Effect of network density and modularity on diffusion in networks publication-title: Proc IEEE 11th Int Conf Data Mining Workshops – start-page: 709 year: 0 ident: ref63 article-title: Mining compressed frequent-pattern sets publication-title: Proc Int Conf Very Large Databases – start-page: 343 year: 0 ident: ref27 article-title: Multilevel K-way hypergraph partitioning publication-title: Proc 36th Annu ACM/IEEE Design Automation Conf – volume: 401 start-page: 130 year: 1999 ident: ref1 article-title: Diameter of the world wide web publication-title: Nature doi: 10.1038/43601 – ident: ref5 doi: 10.1145/948187.948200 – start-page: 1650 year: 0 ident: ref30 article-title: Near-optimal observation selection using submodular functions publication-title: Proc 22nd Nat Conf Artif Intell – ident: ref29 doi: 10.1145/324133.324140 – ident: ref60 doi: 10.1145/1963405.1963508 – start-page: 1 year: 0 ident: ref36 article-title: Social cohesion and embeddedness: A hierarchical conception of social groups publication-title: American Sociologic Review – year: 2012 ident: ref59 article-title: Spreading processes on networks theory and applications – ident: ref28 doi: 10.1145/956750.956769 – ident: ref32 doi: 10.1109/ICDM.2006.149 – ident: ref39 doi: 10.1016/j.socnet.2004.11.009 – ident: ref44 doi: 10.1145/2331042.2331059 – start-page: 418 year: 0 ident: ref54 article-title: Neighborhood formation and anomaly detection in bipartite graphs publication-title: Proc Int Conf Data Mining – ident: ref62 doi: 10.1109/JSAC.2013.130607 – ident: ref65 doi: 10.1086/jar.33.4.3629752 – ident: ref7 doi: 10.1145/1284680.1284681 – ident: ref19 doi: 10.1109/ICDM.2011.132 – year: 2013 ident: ref41 article-title: Interactions on complex networks: Inference algorithms and applications |
| SSID | ssj0008781 |
| Score | 2.4986603 |
| Snippet | Given a large graph, like a computer communication network, which k nodes should we immunize (or monitor, or remove), to make it as robust as possible against... |
| SourceID | crossref ieee |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 113 |
| SubjectTerms | Approximation methods Computational complexity Computers Eigenvalues and eigenfunctions Electronic mail Graph Mining Immune system Immunization Robustness Scalability |
| Title | Node Immunization on Large Graphs: Theory and Algorithms |
| URI | https://ieeexplore.ieee.org/document/7181715 |
| Volume | 28 |
| WOSCitedRecordID | wos000366833100010&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: PRVIEE databaseName: IEEE Electronic Library (IEL) issn: 1041-4347 databaseCode: RIE dateStart: 19890101 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://ieeexplore.ieee.org/ omitProxy: false ssIdentifier: ssj0008781 providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFA5zeNCD001x_iIHT2Jn07RJ623opqIMDxN2K0n6qoPZytb595uk2dhBBKGHUhIoX5u89-X9-BC6tB0IBQEvDHNzdMOkJwOmPKlUTnyhnWYprdgEH43iySR5baDrdS0MANjkM-iZWxvLz0q1NEdlN3ofJdxUlG9xzuparfWuG3MrSKrZheZENOQugkn85Gb8fD8wSVxRLzDdxIyi2oYN2hBVsTZl2Prf2-yjPec74n79sQ9QA4o2aq10GbBbpm20u9FksIPiUZkBfrJ1IHXNJdbXi8kAxw-mXfXiFtcV-lgUGe7P3sv5tPr4XByit-FgfPfoOb0ETwUsqjwIYiYpyxKpjbxgEcS5Xp2-1F6OL6NMBAFQ0OQ5MbFUIojigiSK54pmivo5oUeoWZQFHCPMMhCaO-SSAg0h0Dw5iWWuqZU0HkMcdpG_QjBVrpm40bSYpZZU-ElqQE8N6KkDvYuu1lO-6k4afw3uGMDXAx3WJ78_PkU7erI7GTlDzWq-hHO0rb6r6WJ-Yf-THye2uL8 |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NS8MwGH4ZU1APTjfF-ZmDJ7Fb2vTT29DNjc3iYcJuJUlTHcxWts7fb5J2ZQcRhB5KSUt52uR9n7wfD8Ct7kBITWHYdqK2blxmMMvlBuM8MTGVTjNjWmzCC0N_Ngtea3Bf1cIIIXTymeioUx3LjzO-VltlXbmOmp6qKN9xbNvCRbVWte76npYklfxCsiJie2UM08RBdzp-6qs0LqdjqX5iSlNtywptyapoqzJo_O99juCw9B5Rr_jcx1ATaRMaG2UGVE7UJhxstRlsgR9msUAjXQlSVF0ieUxUDjh6Vg2rVw-oqNFHNI1Rb_GeLef5x-fqBN4G_enj0CgVEwxuuU5uCMt3GXHjgEkzT11H-Imcn5hJPwczJ6aWJYiQ9DlQ0VSTmtyjZsC9hJOYE5yY5BTqaZaKM0BuLKhkDwkjgtjCkkw58FkiyRVTPoNvtwFvEIx42U5cqVosIk0rcBAp0CMFelSC3oa76pavopfGX4NbCvBqYIn1-e-Xb2BvOH2ZRJNROL6Affmgcp_kEur5ci2uYJd_5_PV8lr_Mz_0RbwG |
| 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=Node+Immunization+on+Large+Graphs%3A+Theory+and+Algorithms&rft.jtitle=IEEE+transactions+on+knowledge+and+data+engineering&rft.au=Chen%2C+Chen&rft.au=Tong%2C+Hanghang&rft.au=Prakash%2C+B.+Aditya&rft.au=Tsourakakis%2C+Charalampos+E.&rft.date=2016-01-01&rft.issn=1041-4347&rft.volume=28&rft.issue=1&rft.spage=113&rft.epage=126&rft_id=info:doi/10.1109%2FTKDE.2015.2465378&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TKDE_2015_2465378 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1041-4347&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1041-4347&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1041-4347&client=summon |