{"id":"https://openalex.org/W2962779748","doi":"https://doi.org/10.1145/3132847.3133021","title":"An Attention-based Collaboration Framework for Multi-View Network Representation Learning","display_name":"An Attention-based Collaboration Framework for Multi-View Network Representation Learning","publication_year":2017,"publication_date":"2017-11-06","ids":{"openalex":"https://openalex.org/W2962779748","doi":"https://doi.org/10.1145/3132847.3133021","mag":"2962779748"},"language":"en","primary_location":{"id":"doi:10.1145/3132847.3133021","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3133021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"preprint","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/A5101458727","display_name":"Meng Qu","orcid":"https://orcid.org/0000-0003-2961-8413"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Meng Qu","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077231313","display_name":"Jian Tang","orcid":"https://orcid.org/0000-0002-6819-4185"},"institutions":[{"id":"https://openalex.org/I108192572","display_name":"HEC Montr\u00e9al","ror":"https://ror.org/05ww3wq27","country_code":"CA","type":"education","lineage":["https://openalex.org/I108192572"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jian Tang","raw_affiliation_strings":["HEC Montreal & Montreal Institute of Learning Algorithms, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"HEC Montreal & Montreal Institute of Learning Algorithms, Montreal, Canada","institution_ids":["https://openalex.org/I108192572"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039500313","display_name":"Jingbo Shang","orcid":"https://orcid.org/0000-0002-7249-4404"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingbo Shang","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009408707","display_name":"Xiang Ren","orcid":"https://orcid.org/0000-0001-8655-663X"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Ren","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100642537","display_name":"Ming Zhang","orcid":"https://orcid.org/0000-0002-9809-3430"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019539533","display_name":"Jiawei Han","orcid":"https://orcid.org/0000-0002-3629-2696"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiawei Han","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101458727"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":16.8379,"has_fulltext":false,"cited_by_count":166,"citation_normalized_percentile":{"value":0.99273275,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1767","last_page":"1776"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9939000010490417,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9890999794006348,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7884689569473267},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.7383840084075928},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6631542444229126},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6020352840423584},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5716902613639832},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.5479415059089661},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4958101212978363},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49150121212005615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4897013008594513},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4320250153541565},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40440109372138977}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7884689569473267},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.7383840084075928},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6631542444229126},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6020352840423584},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5716902613639832},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.5479415059089661},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4958101212978363},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49150121212005615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4897013008594513},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4320250153541565},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40440109372138977},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3132847.3133021","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3133021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3297601758","display_name":null,"funder_award_id":"IIS-1320617 and IIS 16-18481","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3339524276","display_name":null,"funder_award_id":"1U54GM114838","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7839634291","display_name":null,"funder_award_id":"61472006, 61772039, 91646202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G948678646","display_name":null,"funder_award_id":"W911NF-09-2-0053","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W950821216","https://openalex.org/W1498436455","https://openalex.org/W1550614472","https://openalex.org/W1586532344","https://openalex.org/W1888005072","https://openalex.org/W2000769684","https://openalex.org/W2010457001","https://openalex.org/W2022322548","https://openalex.org/W2029257328","https://openalex.org/W2037933327","https://openalex.org/W2048679005","https://openalex.org/W2057587538","https://openalex.org/W2068309161","https://openalex.org/W2105924489","https://openalex.org/W2117420919","https://openalex.org/W2118585731","https://openalex.org/W2125031621","https://openalex.org/W2126250169","https://openalex.org/W2133564696","https://openalex.org/W2136294701","https://openalex.org/W2142674578","https://openalex.org/W2145658888","https://openalex.org/W2147527908","https://openalex.org/W2149288670","https://openalex.org/W2153579005","https://openalex.org/W2154415691","https://openalex.org/W2154851992","https://openalex.org/W2158698691","https://openalex.org/W2162941511","https://openalex.org/W2166782149","https://openalex.org/W2405459681","https://openalex.org/W2559655401","https://openalex.org/W2604230684","https://openalex.org/W2604272474","https://openalex.org/W2950133940","https://openalex.org/W2962756421","https://openalex.org/W3001645704","https://openalex.org/W3098040575","https://openalex.org/W3104097132","https://openalex.org/W3104717349","https://openalex.org/W3105705953","https://openalex.org/W6682991666","https://openalex.org/W6717622092"],"related_works":["https://openalex.org/W2032233321","https://openalex.org/W3121970507","https://openalex.org/W2110028391","https://openalex.org/W54497855","https://openalex.org/W217960748","https://openalex.org/W3125814499","https://openalex.org/W2090827041","https://openalex.org/W2565703248","https://openalex.org/W187246281","https://openalex.org/W2143548620"],"abstract_inverted_index":{"Learning":[0],"distributed":[1],"node":[2,63,75,114],"representations":[3,64,76],"in":[4,16,43],"networks":[5,25,55,66,126],"has":[6],"been":[7],"attracting":[8],"increasing":[9],"attention":[10,107],"recently":[11],"due":[12],"to":[13,72,115],"its":[14],"effectiveness":[15],"a":[17,27,36,40,82,141],"variety":[18],"of":[19,30,39,50,91],"applications.":[20],"Existing":[21],"approaches":[22,135,147],"usually":[23,46],"study":[24],"with":[26,56,67,140,148],"single":[28,37,142],"type":[29],"proximity":[31],"between":[32,52],"nodes,":[33,53],"which":[34,70,87,111],"defines":[35],"view":[38,143],"network.":[41],"However,":[42],"reality":[44],"there":[45],"exists":[47],"multiple":[48,57,68,149],"types":[49],"proximities":[51],"yielding":[54],"views.":[58,79,121,150],"This":[59],"paper":[60],"studies":[61],"learning":[62,85,139],"for":[65,98,136],"views,":[69],"aims":[71],"infer":[73],"robust":[74,100],"across":[77],"different":[78,92],"We":[80],"propose":[81],"multi-view":[83],"representation":[84,138],"approach,":[86],"promotes":[88],"the":[89,99,103,118,129],"collaboration":[90],"views":[93],"and":[94,144],"lets":[95],"them":[96],"vote":[97],"representations.":[101],"During":[102],"voting":[104],"process,":[105],"an":[106],"mechanism":[108],"is":[109],"introduced,":[110],"enables":[112],"each":[113],"focus":[116],"on":[117,124],"most":[119],"informative":[120],"Experimental":[122],"results":[123],"real-world":[125],"show":[127],"that":[128],"proposed":[130],"approach":[131],"outperforms":[132],"existing":[133],"state-of-the-art":[134],"network":[137],"other":[145],"competitive":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":28},{"year":2020,"cited_by_count":28},{"year":2019,"cited_by_count":34},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}