{"id":"https://openalex.org/W4318822394","doi":"https://doi.org/10.1109/icdm54844.2022.00124","title":"On Finding and Analyzing the Backbone of the k-Core Structure of a Graph","display_name":"On Finding and Analyzing the Backbone of the k-Core Structure of a Graph","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4318822394","doi":"https://doi.org/10.1109/icdm54844.2022.00124"},"language":"en","primary_location":{"id":"doi:10.1109/icdm54844.2022.00124","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icdm54844.2022.00124","pdf_url":null,"source":{"id":"https://openalex.org/S4363608104","display_name":"2022 IEEE International Conference on Data Mining (ICDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074046047","display_name":"Ricky Laishram","orcid":null},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ricky Laishram","raw_affiliation_strings":["Syracuse University"],"affiliations":[{"raw_affiliation_string":"Syracuse University","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062221607","display_name":"Sucheta Soundarajan","orcid":"https://orcid.org/0000-0003-1166-4067"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sucheta Soundarajan","raw_affiliation_strings":["Syracuse University"],"affiliations":[{"raw_affiliation_string":"Syracuse University","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074046047"],"corresponding_institution_ids":["https://openalex.org/I70983195"],"apc_list":null,"apc_paid":null,"fwci":0.5798,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6378327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"5","issue":null,"first_page":"1017","last_page":"1022"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11476","display_name":"Graph theory and applications","score":0.9733999967575073,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9596999883651733,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.6677930355072021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6166738867759705},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.505620002746582},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.48198312520980835},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4126681685447693},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2174851894378662}],"concepts":[{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.6677930355072021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6166738867759705},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.505620002746582},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48198312520980835},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4126681685447693},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2174851894378662},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm54844.2022.00124","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icdm54844.2022.00124","pdf_url":null,"source":{"id":"https://openalex.org/S4363608104","display_name":"2022 IEEE International Conference on Data Mining (ICDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1587668035","https://openalex.org/W1975360581","https://openalex.org/W1995215995","https://openalex.org/W2094224753","https://openalex.org/W2124725054","https://openalex.org/W2148606255","https://openalex.org/W2162808198","https://openalex.org/W2546574318","https://openalex.org/W2604873699","https://openalex.org/W2788422168","https://openalex.org/W2799128111","https://openalex.org/W2895785599","https://openalex.org/W3013132519","https://openalex.org/W3099460852","https://openalex.org/W3101950588","https://openalex.org/W6635300896"],"related_works":["https://openalex.org/W2363669182","https://openalex.org/W2525150146","https://openalex.org/W2351109918","https://openalex.org/W2391817034","https://openalex.org/W2029791532","https://openalex.org/W2377311228","https://openalex.org/W2737580628","https://openalex.org/W2159447386","https://openalex.org/W1990088789","https://openalex.org/W2109308475"],"abstract_inverted_index":{"In":[0,78],"many":[1],"network":[2,47,76],"applications,":[3,38],"dense":[4,16],"subgraphs":[5],"have":[6,30],"proven":[7],"to":[8,101,112],"be":[9],"extremely":[10],"useful.":[11],"One":[12],"particular":[13],"type":[14],"of":[15,27,36,59,65,71,91,95,138],"subgraph":[17],"known":[18],"as":[19],"the":[20,56,60,63,69,72,83,89,92,129,132,139],"k-core":[21,74,93],"has":[22,54],"received":[23],"a":[24,34,96,115],"great":[25],"deal":[26],"attention.":[28],"k-cores":[29],"been":[31],"used":[32],"in":[33],"number":[35],"important":[37,41],"including":[39,141],"identifying":[40],"nodes,":[42],"speeding":[43],"up":[44],"community":[45],"detection,":[46],"visualization,":[48],"and":[49,62,75,109,127,136],"others.":[50],"However,":[51],"little":[52],"work":[53],"investigated":[55],"\u2018skeletal\u2019":[57],"structure":[58,94],"k-core,":[61],"effect":[64],"such":[66],"structures":[67],"on":[68,105],"properties":[70,137],"overall":[73],"itself.":[77],"this":[79],"paper,":[80],"we":[81],"propose":[82],"Skeletal":[84,120,133],"Core":[85,121,134],"Subgraph,":[86],"which":[87],"describes":[88],"backbone":[90],"graph.":[97],"We":[98,123],"show":[99,124],"how":[100,111],"categorize":[102],"graphs":[103],"based":[104],"their":[106],"skeletal":[107],"cores,":[108],"demonstrate":[110],"efficiently":[113],"decompose":[114],"given":[116],"graph":[117],"into":[118],"its":[119,142],"Subgraph.":[122],"both":[125],"theoretically":[126],"experimentally":[128],"relationship":[130],"between":[131],"Subgraph":[135],"graph,":[140],"core":[143],"resilience.":[144]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}