{"id":"https://openalex.org/W4313423347","doi":"https://doi.org/10.1109/tkde.2022.3233481","title":"A Multi-Type Transferable Method for Missing Link Prediction in Heterogeneous Social Networks","display_name":"A Multi-Type Transferable Method for Missing Link Prediction in Heterogeneous Social Networks","publication_year":2023,"publication_date":"2023-01-02","ids":{"openalex":"https://openalex.org/W4313423347","doi":"https://doi.org/10.1109/tkde.2022.3233481"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3233481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3233481","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research-repository.st-andrews.ac.uk/bitstream/10023/26701/1/Wang_2022_A_multi_type_transferable_method_IEETKDE_AAM.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054184997","display_name":"Huan Wang","orcid":"https://orcid.org/0000-0002-3162-2350"},"institutions":[{"id":"https://openalex.org/I204823248","display_name":"Huazhong Agricultural University","ror":"https://ror.org/023b72294","country_code":"CN","type":"education","lineage":["https://openalex.org/I204823248"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huan Wang","raw_affiliation_strings":["College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I204823248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010769217","display_name":"Ziwen Cui","orcid":"https://orcid.org/0000-0001-7867-3692"},"institutions":[{"id":"https://openalex.org/I204823248","display_name":"Huazhong Agricultural University","ror":"https://ror.org/023b72294","country_code":"CN","type":"education","lineage":["https://openalex.org/I204823248"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziwen Cui","raw_affiliation_strings":["College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I204823248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101767083","display_name":"Ruigang Liu","orcid":"https://orcid.org/0009-0000-8750-3919"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruigang Liu","raw_affiliation_strings":["China Mobile (Hangzhou) Information Technology Co., Ltd., Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"China Mobile (Hangzhou) Information Technology Co., Ltd., Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101624499","display_name":"Lei Fang","orcid":"https://orcid.org/0000-0003-3624-371X"},"institutions":[{"id":"https://openalex.org/I16835326","display_name":"University of St Andrews","ror":"https://ror.org/02wn5qz54","country_code":"GB","type":"education","lineage":["https://openalex.org/I16835326"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lei Fang","raw_affiliation_strings":["School of Computer Science, University of St Andrews, Scotland, U.K"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of St Andrews, Scotland, U.K","institution_ids":["https://openalex.org/I16835326"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025938663","display_name":"Ying Sha","orcid":"https://orcid.org/0000-0002-6638-5009"},"institutions":[{"id":"https://openalex.org/I204823248","display_name":"Huazhong Agricultural University","ror":"https://ror.org/023b72294","country_code":"CN","type":"education","lineage":["https://openalex.org/I204823248"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Sha","raw_affiliation_strings":["College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I204823248"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5054184997"],"corresponding_institution_ids":["https://openalex.org/I204823248"],"apc_list":null,"apc_paid":null,"fwci":16.1812,"has_fulltext":false,"cited_by_count":93,"citation_normalized_percentile":{"value":0.9939987,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"35","issue":"11","first_page":"10981","last_page":"10991"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9915000200271606,"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/discriminative-model","display_name":"Discriminative model","score":0.861392080783844},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7473037838935852},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7330195903778076},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6870219111442566},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6547352075576782},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6394036412239075},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5259164571762085},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4873810410499573},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4379955530166626},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2945448160171509}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.861392080783844},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7473037838935852},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7330195903778076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6870219111442566},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6547352075576782},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6394036412239075},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5259164571762085},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4873810410499573},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4379955530166626},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2945448160171509}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2022.3233481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3233481","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:research-repository.st-andrews.ac.uk:10023/26701","is_oa":true,"landing_page_url":"https://hdl.handle.net/10023/26701","pdf_url":"https://research-repository.st-andrews.ac.uk/bitstream/10023/26701/1/Wang_2022_A_multi_type_transferable_method_IEETKDE_AAM.pdf","source":{"id":"https://openalex.org/S4306400230","display_name":"St Andrews Research Repository (St Andrews Research Repository)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16835326","host_organization_name":"University of St Andrews","host_organization_lineage":["https://openalex.org/I16835326"],"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":"Journal article"}],"best_oa_location":{"id":"pmh:oai:research-repository.st-andrews.ac.uk:10023/26701","is_oa":true,"landing_page_url":"https://hdl.handle.net/10023/26701","pdf_url":"https://research-repository.st-andrews.ac.uk/bitstream/10023/26701/1/Wang_2022_A_multi_type_transferable_method_IEETKDE_AAM.pdf","source":{"id":"https://openalex.org/S4306400230","display_name":"St Andrews Research Repository (St Andrews Research Repository)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16835326","host_organization_name":"University of St Andrews","host_organization_lineage":["https://openalex.org/I16835326"],"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":"Journal article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G2935348012","display_name":null,"funder_award_id":"62102265","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4089291737","display_name":null,"funder_award_id":"2662019QD047","funder_id":"https://openalex.org/F4320324775","funder_display_name":"Huazhong Agricultural University"},{"id":"https://openalex.org/G5719134295","display_name":null,"funder_award_id":"62272188","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G683915605","display_name":null,"funder_award_id":"62006089","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/F4320324775","display_name":"Huazhong Agricultural University","ror":"https://ror.org/023b72294"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4313423347.pdf"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W1501299699","https://openalex.org/W1882958252","https://openalex.org/W1964940342","https://openalex.org/W1967531152","https://openalex.org/W1971421925","https://openalex.org/W1977382765","https://openalex.org/W2016621483","https://openalex.org/W2064503471","https://openalex.org/W2101900104","https://openalex.org/W2109298920","https://openalex.org/W2118440866","https://openalex.org/W2126185296","https://openalex.org/W2157825442","https://openalex.org/W2167467982","https://openalex.org/W2521812403","https://openalex.org/W2533282150","https://openalex.org/W2609338674","https://openalex.org/W2736566518","https://openalex.org/W2743104969","https://openalex.org/W2765811365","https://openalex.org/W2809645418","https://openalex.org/W2892341857","https://openalex.org/W2908732234","https://openalex.org/W2941287638","https://openalex.org/W2945266622","https://openalex.org/W2951050019","https://openalex.org/W2952343887","https://openalex.org/W2962756421","https://openalex.org/W2963707260","https://openalex.org/W2963757395","https://openalex.org/W2963919031","https://openalex.org/W2965857891","https://openalex.org/W2986416218","https://openalex.org/W2995868056","https://openalex.org/W3004507689","https://openalex.org/W3006318668","https://openalex.org/W3012871709","https://openalex.org/W3037988456","https://openalex.org/W3080152140","https://openalex.org/W3082268164","https://openalex.org/W3089140681","https://openalex.org/W3093861821","https://openalex.org/W3097982973","https://openalex.org/W3100863972","https://openalex.org/W3103513278","https://openalex.org/W3103814605","https://openalex.org/W3134531423","https://openalex.org/W3156968278","https://openalex.org/W3172515294","https://openalex.org/W3189626311","https://openalex.org/W3204140782","https://openalex.org/W4205911334","https://openalex.org/W4288101963","https://openalex.org/W6639480849","https://openalex.org/W6748856961","https://openalex.org/W6768533090","https://openalex.org/W6783190758","https://openalex.org/W6799831306"],"related_works":["https://openalex.org/W4396941953","https://openalex.org/W2093104230","https://openalex.org/W2987280934","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W2128027845","https://openalex.org/W3014948380","https://openalex.org/W4386184937","https://openalex.org/W4394728283"],"abstract_inverted_index":{"Heterogeneous":[0],"social":[1,47,80,229],"networks,":[2,81],"which":[3,82,161],"are":[4,43,173],"characterized":[5],"by":[6,138],"diverse":[7],"interaction":[8],"types,":[9,160],"have":[10],"resulted":[11],"in":[12,45,78,227],"new":[13],"challenges":[14],"for":[15,74,122,223],"missing":[16,41,75,117,200,224],"link":[17,35,76,107,114,124,144,159,176,208,225],"prediction.":[18],"Most":[19],"deep":[20,56],"learning":[21,57,139],"models":[22],"tend":[23],"to":[24,28,87,126,133,149,156,198],"capture":[25],"type-specific":[26],"features":[27],"maximize":[29],"the":[30,38,51,112,128,135,152,164,169,179,192,214],"prediction":[31,52,77,129,226],"performances":[32,53],"on":[33,186,203],"specific":[34],"types.":[36,145,177,209],"However,":[37],"types":[39,125],"of":[40,54],"links":[42,201],"uncertain":[44],"heterogeneous":[46,79,228],"networks;":[48],"this":[49,61,187],"restricts":[50],"existing":[55],"models.":[58],"To":[59,119],"address":[60],"issue,":[62],"we":[63],"propose":[64],"a":[65,95,99,116],"multi-type":[66],"transferable":[67,140,174,204],"method":[68],"(":[69],"<italic":[70,181,216],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[71,182,217],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">MTTM</i>":[72,183,218],")":[73],"exploits":[83],"adversarial":[84],"neural":[85],"networks":[86],"remain":[88],"robust":[89],"against":[90],"type":[91],"differences.":[92],"It":[93],"comprises":[94],"generative":[96,103,165,193],"predictor":[97,104,166,194],"and":[98,109,195],"discriminative":[100,136,153,196],"classifier.":[101],"The":[102],"can":[105,219],"extract":[106],"representations":[108,142,172,206],"predict":[110,199],"whether":[111,168],"unobserved":[113],"is":[115,184],"link.":[118],"generalize":[120],"well":[121],"different":[123],"improve":[127],"performance,":[130],"it":[131],"attempts":[132,155],"deceive":[134],"classifier":[137,154,197],"feature":[141,171,205],"among":[143,175,207],"In":[146],"order":[147],"not":[148],"be":[150],"deceived,":[151],"accurately":[157],"distinguish":[158],"indirectly":[162],"helps":[163],"judge":[167],"learned":[170],"Finally,":[178],"integrated":[180],"constructed":[185],"minimax":[188],"two-player":[189],"game":[190],"between":[191],"based":[202],"Extensive":[210],"experiments":[211],"show":[212],"that":[213],"proposed":[215],"outperform":[220],"state-of-the-art":[221],"baselines":[222],"networks.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":26}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
