{"id":"https://openalex.org/W2921266846","doi":"https://doi.org/10.1007/s41109-019-0162-z","title":"Ensemble clustering for graphs: comparisons and applications","display_name":"Ensemble clustering for graphs: comparisons and applications","publication_year":2019,"publication_date":"2019-07-22","ids":{"openalex":"https://openalex.org/W2921266846","doi":"https://doi.org/10.1007/s41109-019-0162-z","mag":"2921266846"},"language":"en","primary_location":{"id":"doi:10.1007/s41109-019-0162-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41109-019-0162-z","pdf_url":"https://appliednetsci.springeropen.com/track/pdf/10.1007/s41109-019-0162-z","source":{"id":"https://openalex.org/S3035517252","display_name":"Applied Network Science","issn_l":"2364-8228","issn":["2364-8228"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Network Science","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://appliednetsci.springeropen.com/track/pdf/10.1007/s41109-019-0162-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Val\u00e9rie Poulin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Val\u00e9rie Poulin","raw_affiliation_strings":["Tutte Institute for Mathematics and Computing, Ottawa, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tutte Institute for Mathematics and Computing, Ottawa, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Fran\u00e7ois Th\u00e9berge","orcid":"https://orcid.org/0000-0002-5499-3680"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fran\u00e7ois Th\u00e9berge","raw_affiliation_strings":["Tutte Institute for Mathematics and Computing, Ottawa, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5499-3680","affiliations":[{"raw_affiliation_string":"Tutte Institute for Mathematics and Computing, Ottawa, Canada","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":790,"currency":"GBP","value_usd":969},"apc_paid":{"value":790,"currency":"GBP","value_usd":969},"fwci":1.4419,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.81489954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"4","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.5149000287055969,"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":0.5149000287055969,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.2872999906539917,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.04800000041723251,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6887999773025513},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6069999933242798},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.558899998664856},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5385000109672546},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5299999713897705},{"id":"https://openalex.org/keywords/zoom","display_name":"Zoom","score":0.5200999975204468},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4848000109195709},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.4794999957084656}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6887999773025513},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6133000254631042},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6069999933242798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6014000177383423},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.558899998664856},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5385000109672546},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5299999713897705},{"id":"https://openalex.org/C124913957","wikidata":"https://www.wikidata.org/wiki/Q1232548","display_name":"Zoom","level":3,"score":0.5200999975204468},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4848000109195709},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.4794999957084656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43130001425743103},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32120001316070557},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.31679999828338623},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2872999906539917},{"id":"https://openalex.org/C111442797","wikidata":"https://www.wikidata.org/wiki/Q7291446","display_name":"Rand index","level":3,"score":0.2806999981403351},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.274399995803833},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2644999921321869}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s41109-019-0162-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41109-019-0162-z","pdf_url":"https://appliednetsci.springeropen.com/track/pdf/10.1007/s41109-019-0162-z","source":{"id":"https://openalex.org/S3035517252","display_name":"Applied Network Science","issn_l":"2364-8228","issn":["2364-8228"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Network Science","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1903.08012","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.08012","pdf_url":"https://arxiv.org/pdf/1903.08012","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:5e3878212f8b46aa986c2d09122132c6","is_oa":true,"landing_page_url":"https://doaj.org/article/5e3878212f8b46aa986c2d09122132c6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Network Science, Vol 4, Iss 1, Pp 1-13 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41109-019-0162-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41109-019-0162-z","pdf_url":"https://appliednetsci.springeropen.com/track/pdf/10.1007/s41109-019-0162-z","source":{"id":"https://openalex.org/S3035517252","display_name":"Applied Network Science","issn_l":"2364-8228","issn":["2364-8228"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Network Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2921266846.pdf","grobid_xml":"https://content.openalex.org/works/W2921266846.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W183430139","https://openalex.org/W1971421925","https://openalex.org/W1973377476","https://openalex.org/W1975959061","https://openalex.org/W1991408655","https://openalex.org/W2015953751","https://openalex.org/W2023655578","https://openalex.org/W2025543856","https://openalex.org/W2047940964","https://openalex.org/W2070746915","https://openalex.org/W2113054345","https://openalex.org/W2128366083","https://openalex.org/W2131681506","https://openalex.org/W2132202037","https://openalex.org/W2148606196","https://openalex.org/W2164998314","https://openalex.org/W2177037623","https://openalex.org/W2497752945","https://openalex.org/W2807249408","https://openalex.org/W2951271819","https://openalex.org/W2964020405","https://openalex.org/W4292081303","https://openalex.org/W6926322381"],"related_works":[],"abstract_inverted_index":{"We":[0,46,67],"recently":[1],"proposed":[2],"a":[3,48,65,69,86,124],"new":[4],"ensemble":[5],"clustering":[6],"algorithm":[7],"for":[8],"graphs":[9],"(ECG)":[10],"based":[11,52,95],"on":[12,53,96,130],"the":[13,26,31,44,59,81,105,131],"concept":[14],"of":[15,43,61,72,83,88,104],"consensus":[16],"clustering.":[17],"In":[18,90],"this":[19],"paper,":[20],"we":[21,92,108,116],"provide":[22],"experimental":[23],"evidence":[24],"to":[25,40,56,111,127],"claim":[27],"that":[28,37,118],"ECG":[29,54,84,110,119],"alleviates":[30],"well-known":[32],"resolution":[33],"limit":[34],"issue,":[35],"and":[36,77,107],"it":[38],"leads":[39],"better":[41],"stability":[42],"partitions.":[45],"propose":[47],"community":[49,62],"strength":[50],"index":[51],"results":[55],"help":[57],"quantify":[58],"presence":[60],"structure":[63,103],"in":[64,123,129],"graph.":[66],"perform":[68],"wide":[70],"range":[71],"experiments":[73],"both":[74],"over":[75,85],"synthetic":[76],"real":[78],"graphs,":[79],"showing":[80],"usefulness":[82],"variety":[87],"problems.":[89],"particular,":[91],"consider":[93],"measures":[94],"node":[97],"partitions":[98],"as":[99,101],"well":[100],"topological":[102],"communities,":[106],"apply":[109],"community-aware":[112],"anomaly":[113],"detection.":[114],"Finally,":[115],"show":[117],"can":[120],"be":[121],"used":[122],"semi-supervised":[125],"context":[126],"zoom":[128],"sub-graph":[132],"most":[133],"closely":[134],"associated":[135],"with":[136],"seed":[137],"nodes.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2019-03-22T00:00:00"}