{"id":"https://openalex.org/W3167595471","doi":"https://doi.org/10.1145/3447548.3467443","title":"Semi-Supervised Deep Learning for Multiplex Networks","display_name":"Semi-Supervised Deep Learning for Multiplex Networks","publication_year":2021,"publication_date":"2021-08-13","ids":{"openalex":"https://openalex.org/W3167595471","doi":"https://doi.org/10.1145/3447548.3467443","mag":"3167595471"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467443","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","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/A5074601218","display_name":"Anasua Mitra","orcid":null},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Anasua Mitra","raw_affiliation_strings":["Indian Institute of Technology Guwahati, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Guwahati, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030820031","display_name":"Priyesh Vijayan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Priyesh Vijayan","raw_affiliation_strings":["McGill university &amp; Mila, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"McGill university &amp; Mila, Montreal, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049027528","display_name":"Ranbir Sanasam","orcid":null},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ranbir Sanasam","raw_affiliation_strings":["Indian Institute of Technology Guwahati, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Guwahati, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102034516","display_name":"Diganta Goswami","orcid":null},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Diganta Goswami","raw_affiliation_strings":["Indian Institute of Technology Guwahati, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Guwahati, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100755351","display_name":"Srinivasan Parthasarathy","orcid":"https://orcid.org/0000-0002-6062-6449"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinivasan Parthasarathy","raw_affiliation_strings":["Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009374923","display_name":"Balaraman Ravindran","orcid":"https://orcid.org/0000-0002-5364-7639"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Balaraman Ravindran","raw_affiliation_strings":["Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5074601218"],"corresponding_institution_ids":["https://openalex.org/I1317621060"],"apc_list":null,"apc_paid":null,"fwci":1.9562,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88468673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1234","last_page":"1244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9993000030517578,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9980999827384949,"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/computer-science","display_name":"Computer science","score":0.7915761470794678},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6001162528991699},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5938889980316162},{"id":"https://openalex.org/keywords/multiplex","display_name":"Multiplex","score":0.5621105432510376},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.547853410243988},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5042001008987427},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4870303273200989},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.47643715143203735},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4677080512046814},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4510018229484558},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43543678522109985},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.425266295671463},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41607633233070374},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.41449469327926636},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4121229648590088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7915761470794678},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6001162528991699},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5938889980316162},{"id":"https://openalex.org/C2781188995","wikidata":"https://www.wikidata.org/wiki/Q6934982","display_name":"Multiplex","level":2,"score":0.5621105432510376},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.547853410243988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5042001008987427},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4870303273200989},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.47643715143203735},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4677080512046814},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4510018229484558},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43543678522109985},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.425266295671463},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41607633233070374},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.41449469327926636},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4121229648590088},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467443","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1661538021","display_name":null,"funder_award_id":"SES-1949037, OAC-2018627, CCF-2028944","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320307102","display_name":"Intel Corporation","ror":"https://ror.org/01ek73717"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1532325895","https://openalex.org/W2102848467","https://openalex.org/W2294501066","https://openalex.org/W2393319904","https://openalex.org/W2405933695","https://openalex.org/W2604942799","https://openalex.org/W2786016794","https://openalex.org/W2788816357","https://openalex.org/W2789042518","https://openalex.org/W2798673265","https://openalex.org/W2801116648","https://openalex.org/W2808361044","https://openalex.org/W2907492528","https://openalex.org/W2911286998","https://openalex.org/W2963127791","https://openalex.org/W2963920355","https://openalex.org/W2969212296","https://openalex.org/W2997686727","https://openalex.org/W2997932753","https://openalex.org/W3014017986","https://openalex.org/W3037826211","https://openalex.org/W3087257704","https://openalex.org/W3103659988","https://openalex.org/W4210257598","https://openalex.org/W6736262870","https://openalex.org/W6752637540"],"related_works":["https://openalex.org/W2087421209","https://openalex.org/W3006199032","https://openalex.org/W1963826946","https://openalex.org/W2559664082","https://openalex.org/W2547948671","https://openalex.org/W4281783318","https://openalex.org/W2023853334","https://openalex.org/W2098964748","https://openalex.org/W2129331923","https://openalex.org/W4362637502"],"abstract_inverted_index":{"Multiplex":[0],"networks":[1,137],"are":[2,12,30],"complex":[3,35],"graph":[4,75,93],"structures":[5,83],"in":[6,122],"which":[7],"a":[8,25,46,88,109,123],"set":[9],"of":[10,20,100,108,125],"entities":[11],"connected":[13],"to":[14,32,77],"each":[15,22],"other":[16],"via":[17],"multiple":[18],"types":[19],"relations,":[21],"relation":[23],"representing":[24],"distinct":[26],"layer.":[27],"Such":[28],"graphs":[29],"used":[31],"investigate":[33],"many":[34],"biological,":[36],"social,":[37],"and":[38,70,81,102,130],"technological":[39],"systems.":[40],"In":[41],"this":[42],"work,":[43],"we":[44,113],"present":[45],"novel":[47,89],"semi-supervised":[48],"approach":[49,58],"for":[50,97,138],"structure-aware":[51,73],"representation":[52],"learning":[53],"on":[54,60,133],"multiplex":[55,110,136],"networks.":[56],"Our":[57],"relies":[59],"maximizing":[61],"the":[62,79,106,116],"mutual":[63],"information":[64],"between":[65],"local":[66],"node-wise":[67],"patch":[68],"representations":[69,76,104],"label":[71],"correlated":[72],"global":[74,92],"model":[78],"nodes":[80],"cluster":[82,103],"jointly.":[84],"Specifically,":[85],"it":[86],"leverages":[87],"cluster-aware,":[90],"node-contextualized":[91],"summary":[94],"generation":[95],"strategy":[96],"effective":[98],"joint-modeling":[99],"node":[101],"across":[105],"layers":[107],"network.":[111],"Empirically,":[112],"demonstrate":[114],"that":[115],"proposed":[117],"architecture":[118],"outperforms":[119],"state-of-the-art":[120],"methods":[121],"range":[124],"tasks:":[126],"classification,":[127],"clustering,":[128],"visualization,":[129],"similarity":[131],"search":[132],"seven":[134],"real-world":[135],"various":[139],"experiment":[140],"settings.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-08T08:50:53.379069","created_date":"2025-10-10T00:00:00"}
