{"id":"https://openalex.org/W4214899340","doi":"https://doi.org/10.1109/tnnls.2022.3149997","title":"Analyzing Heterogeneous Networks With Missing Attributes by Unsupervised Contrastive Learning","display_name":"Analyzing Heterogeneous Networks With Missing Attributes by Unsupervised Contrastive Learning","publication_year":2022,"publication_date":"2022-03-02","ids":{"openalex":"https://openalex.org/W4214899340","doi":"https://doi.org/10.1109/tnnls.2022.3149997","pmid":"https://pubmed.ncbi.nlm.nih.gov/35235523"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3149997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3149997","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Dongxiao He","orcid":"https://orcid.org/0000-0002-1915-4179"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxiao He","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-1915-4179","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chundong Liang","orcid":"https://orcid.org/0000-0002-8350-353X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chundong Liang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8350-353X","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Cuiying Huo","orcid":"https://orcid.org/0000-0003-4914-4577"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cuiying Huo","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-4914-4577","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhiyong Feng","orcid":"https://orcid.org/0000-0001-8158-7453"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Feng","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-8158-7453","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Di Jin","orcid":"https://orcid.org/0000-0002-7445-9936"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Jin","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-7445-9936","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Liang Yang","orcid":"https://orcid.org/0000-0001-6291-4359"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Yang","raw_affiliation_strings":["School of Artificial Intelligence, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-6291-4359","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":null,"display_name":"Weixiong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Weixiong Zhang","raw_affiliation_strings":["Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.5218,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.95188926,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"35","issue":"4","first_page":"4438","last_page":"4450"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9815000295639038,"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":0.9815000295639038,"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":0.0020000000949949026,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.0020000000949949026,"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/unsupervised-learning","display_name":"Unsupervised learning","score":0.5637999773025513},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5131000280380249},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5058000087738037},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.489300012588501},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.3921999931335449},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.37929999828338623},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.3736000061035156},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.3370000123977661}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7508999705314636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6958000063896179},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5637999773025513},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5131000280380249},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4909999966621399},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.489300012588501},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.3921999931335449},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.37929999828338623},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3736000061035156},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3684000074863434},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.3370000123977661},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28220000863075256},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.26019999384880066}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3149997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3149997","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35235523","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35235523","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G356530974","display_name":null,"funder_award_id":"2019YFB2102404","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3628717404","display_name":"\u9762\u5411\u5f02\u6784\u62d3\u6251\u4e0e\u8bed\u4e49\u878d\u5408\u7684\u5927\u89c4\u6a21\u7f51\u7edc\u5212\u5206\u7814\u7a76","funder_award_id":"61972442","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3991582358","display_name":null,"funder_award_id":"F2020202040","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"},{"id":"https://openalex.org/G4857815385","display_name":null,"funder_award_id":"20JCYBJC00650","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G6134627929","display_name":null,"funder_award_id":"61832014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G678178878","display_name":null,"funder_award_id":"61876128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8451749416","display_name":"\u9762\u5411\u5927\u89c4\u6a21\u3001\u5e26\u5185\u5bb9\u590d\u6742\u7f51\u7edc\u7684\u7cbe\u51c6\u8bed\u4e49\u793e\u56e2\u53d1\u73b0\u7814\u7a76","funder_award_id":"61772361","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W2023026264","https://openalex.org/W2075010670","https://openalex.org/W2593414223","https://openalex.org/W2604314403","https://openalex.org/W2743104969","https://openalex.org/W2903634148","https://openalex.org/W2907492528","https://openalex.org/W2911286998","https://openalex.org/W2950880273","https://openalex.org/W2963919031","https://openalex.org/W2965857891","https://openalex.org/W2997461192","https://openalex.org/W2998423439","https://openalex.org/W3004507689","https://openalex.org/W3012816161","https://openalex.org/W3012871709","https://openalex.org/W3016163458","https://openalex.org/W3035719901","https://openalex.org/W3036446966","https://openalex.org/W3040731923","https://openalex.org/W3092835783","https://openalex.org/W3095746859","https://openalex.org/W3096655658","https://openalex.org/W3114632476","https://openalex.org/W3127541398","https://openalex.org/W3134210100","https://openalex.org/W3155314443","https://openalex.org/W3155886566","https://openalex.org/W3172710079","https://openalex.org/W3183241772","https://openalex.org/W3194841521","https://openalex.org/W3199755688","https://openalex.org/W4207040171","https://openalex.org/W4385245566","https://openalex.org/W4385819812","https://openalex.org/W6636510571","https://openalex.org/W6637568146","https://openalex.org/W6638523607","https://openalex.org/W6726873649","https://openalex.org/W6729323343","https://openalex.org/W6730084236","https://openalex.org/W6741832134","https://openalex.org/W6745537798","https://openalex.org/W6751751081","https://openalex.org/W6752051073","https://openalex.org/W6755573351","https://openalex.org/W6767098714","https://openalex.org/W6769589523","https://openalex.org/W6774314701","https://openalex.org/W6779940601","https://openalex.org/W6779997284","https://openalex.org/W6784694379","https://openalex.org/W6784776072","https://openalex.org/W6785554234","https://openalex.org/W6795898371"],"related_works":[],"abstract_inverted_index":{"Heterogeneous":[0],"information":[1],"networks":[2],"(HINs)":[3],"are":[4],"potent":[5],"models":[6],"of":[7,72,78,113,133],"complex":[8],"systems.":[9],"In":[10],"practice,":[11],"many":[12],"nodes":[13,94],"in":[14,22,61,80],"an":[15,34,62,85],"HIN":[16,135],"have":[17],"their":[18],"attributes":[19,46,74,96,126],"unspecified,":[20],"resulting":[21],"significant":[23],"performance":[24,132],"degradation":[25],"for":[26,41],"supervised":[27],"and":[28,58,75,95],"unsupervised":[29,35,63,81],"representation":[30,59],"learning.":[31],"We":[32],"developed":[33],"heterogeneous":[36,64],"graph":[37],"contrastive":[38,51],"learning":[39,52,60],"approach":[40],"analyzing":[42],"HINs":[43,109],"with":[44,68],"missing":[45,73],"(HGCA).":[47],"HGCA":[48,114,128],"adopts":[49],"a":[50,69,99],"strategy":[53],"to":[54,88,97],"unify":[55],"attribute":[56,101],"completion":[57],"framework.":[65],"To":[66],"deal":[67],"large":[70,107],"number":[71],"the":[76,90,111,124,131],"absence":[77],"labels":[79],"scenarios,":[82],"we":[83],"proposed":[84],"augmented":[86],"network":[87],"capture":[89],"semantic":[91],"relations":[92],"between":[93],"achieve":[98],"fine-grained":[100],"completion.":[102],"Extensive":[103],"experiments":[104],"on":[105],"three":[106],"real-world":[108],"demonstrated":[110],"superiority":[112],"over":[115],"several":[116],"state-of-the-art":[117],"methods.":[118],"The":[119],"results":[120],"also":[121],"showed":[122],"that":[123],"complemented":[125],"by":[127],"can":[129],"improve":[130],"existing":[134],"models.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2022-03-05T00:00:00"}
