{"id":"https://openalex.org/W788502760","doi":"https://doi.org/10.1145/2808797.2808852","title":"Community Detection in Multiplex Networks using Locally Adaptive Random Walks","display_name":"Community Detection in Multiplex Networks using Locally Adaptive Random Walks","publication_year":2015,"publication_date":"2015-08-25","ids":{"openalex":"https://openalex.org/W788502760","doi":"https://doi.org/10.1145/2808797.2808852","mag":"788502760"},"language":"en","primary_location":{"id":"doi:10.1145/2808797.2808852","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808797.2808852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015","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/A5040943287","display_name":"Zhana Kuncheva","orcid":"https://orcid.org/0000-0003-4057-6525"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhana Kuncheva","raw_affiliation_strings":["Department of Mathematics, Imperial College London","Dept. of Mathematics, Imperial College, London#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Imperial College London","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Dept. of Mathematics, Imperial College, London#TAB#","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010581004","display_name":"Giovanni Montana","orcid":"https://orcid.org/0000-0003-3942-3900"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Giovanni Montana","raw_affiliation_strings":["Department of Biomedical Engineering, King's College Londone"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, King's College Londone","institution_ids":["https://openalex.org/I183935753"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.0086,"has_fulltext":false,"cited_by_count":82,"citation_normalized_percentile":{"value":0.95391536,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1308","last_page":"1315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9940000176429749,"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/T10742","display_name":"Peer-to-Peer Network Technologies","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/random-walk","display_name":"Random walk","score":0.8120716214179993},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7121962308883667},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6905596852302551},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.5799188017845154},{"id":"https://openalex.org/keywords/multiplex","display_name":"Multiplex","score":0.5540465712547302},{"id":"https://openalex.org/keywords/community-structure","display_name":"Community structure","score":0.522556483745575},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5092421770095825},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4520646035671234},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40682676434516907},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3973936140537262},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2861149311065674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16697484254837036},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09419497847557068},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08705145120620728},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07916590571403503}],"concepts":[{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.8120716214179993},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7121962308883667},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6905596852302551},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.5799188017845154},{"id":"https://openalex.org/C2781188995","wikidata":"https://www.wikidata.org/wiki/Q6934982","display_name":"Multiplex","level":2,"score":0.5540465712547302},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.522556483745575},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5092421770095825},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4520646035671234},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40682676434516907},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3973936140537262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2861149311065674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16697484254837036},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09419497847557068},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08705145120620728},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07916590571403503},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2808797.2808852","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808797.2808852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015","raw_type":"proceedings-article"},{"id":"pmh:oai:kclpure.kcl.ac.uk:publications/3f76bec7-9def-45da-965a-13f3117fd8dc","is_oa":false,"landing_page_url":"https://kclpure.kcl.ac.uk/portal/en/publications/3f76bec7-9def-45da-965a-13f3117fd8dc","pdf_url":null,"source":{"id":"https://openalex.org/S4306400216","display_name":"Research Portal (King's College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183935753","host_organization_name":"King's College London","host_organization_lineage":["https://openalex.org/I183935753"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kuncheva, Z & Montana, G 2015, Community detection in multiplex networks using Locally Adaptive Random walks. in Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015. pp. 1308-1315, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Paris, France, 25/08/2015. https://doi.org/10.1145/2808797.2808852","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5199999809265137,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W33790260","https://openalex.org/W187552706","https://openalex.org/W1514107797","https://openalex.org/W1535365835","https://openalex.org/W1647431324","https://openalex.org/W1655843738","https://openalex.org/W1807089695","https://openalex.org/W1812137573","https://openalex.org/W1971421925","https://openalex.org/W1974843168","https://openalex.org/W1987515125","https://openalex.org/W1988515336","https://openalex.org/W2004843357","https://openalex.org/W2005941514","https://openalex.org/W2012685480","https://openalex.org/W2030644393","https://openalex.org/W2031886776","https://openalex.org/W2068667499","https://openalex.org/W2074617510","https://openalex.org/W2095711515","https://openalex.org/W2097645701","https://openalex.org/W2098005762","https://openalex.org/W2098509290","https://openalex.org/W2127048411","https://openalex.org/W2147475342","https://openalex.org/W2150049940","https://openalex.org/W2161503382","https://openalex.org/W2164727176","https://openalex.org/W2164998314","https://openalex.org/W2165232124","https://openalex.org/W2950655917","https://openalex.org/W2963155478","https://openalex.org/W3037826211","https://openalex.org/W3102201777","https://openalex.org/W3102641634","https://openalex.org/W3103589660","https://openalex.org/W3106488715","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2960185556","https://openalex.org/W2585421148","https://openalex.org/W2904470306","https://openalex.org/W2971077813","https://openalex.org/W1641227098","https://openalex.org/W4311620446","https://openalex.org/W4220973966","https://openalex.org/W2067674661","https://openalex.org/W4286377521","https://openalex.org/W2952609329"],"abstract_inverted_index":{"Multiplex":[0],"networks,":[1,7],"a":[2,56,88,132,147],"special":[3],"type":[4],"of":[5,30,68,123,164],"multilayer":[6],"are":[8,46,71,102,140],"increasingly":[9],"applied":[10],"in":[11,24,39,80,146,166],"many":[12],"domains":[13],"ranging":[14],"from":[15],"social":[16],"media":[17],"analytics":[18],"to":[19,42,104,119,160,168],"biology.":[20],"A":[21],"common":[22],"task":[23],"these":[25],"applications":[26],"concerns":[27],"the":[28,66,78,81,92,95,99,107,121,162],"detection":[29,38,58,67,171],"community":[31,37,57,170],"structures.":[32],"Many":[33],"existing":[34],"algorithms":[35],"for":[36,65],"multiplexes":[40],"attempt":[41],"detect":[43],"communities":[44,69,124],"which":[45],"shared":[47,72],"by":[48,73],"all":[49,77],"layers.":[50,126],"In":[51],"this":[52,129,144],"article":[53],"we":[54],"propose":[55],"algorithm,":[59],"LART":[60,165],"(Locally":[61],"Adaptive":[62],"Random":[63],"Transitions),":[64],"that":[70],"either":[74],"some":[75],"or":[76],"layers":[79,112],"multiplex.":[82],"The":[83],"algorithm":[84],"is":[85,136],"based":[86,142],"on":[87,91,106,128,143],"random":[89,100,130],"walk":[90,101],"multiplex,":[93],"and":[94,138],"transition":[96],"probabilities":[97],"defining":[98],"allowed":[103],"depend":[105],"local":[108],"topological":[109],"similarity":[110],"between":[111],"at":[113],"any":[114],"given":[115],"node":[116,133],"so":[117],"as":[118],"facilitate":[120],"exploration":[122],"across":[125],"Based":[127],"walk,":[131],"dissimilarity":[134],"measure":[135],"derived":[137],"nodes":[139],"clustered":[141],"distance":[145],"hierarchical":[148],"fashion.":[149],"We":[150],"present":[151],"experimental":[152],"results":[153],"using":[154],"networks":[155],"simulated":[156],"under":[157],"various":[158],"scenarios":[159],"showcase":[161],"performance":[163],"comparison":[167],"related":[169],"algorithms.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}