{"id":"https://openalex.org/W4295788917","doi":"https://doi.org/10.1109/tkde.2022.3206597","title":"PF-HIN:Pre-Training for Heterogeneous Information Networks","display_name":"PF-HIN:Pre-Training for Heterogeneous Information Networks","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4295788917","doi":"https://doi.org/10.1109/tkde.2022.3206597"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3206597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3206597","pdf_url":"https://ieeexplore.ieee.org/ielx7/69/4358933/09891783.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/69/4358933/09891783.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004606411","display_name":"Yang Fang","orcid":"https://orcid.org/0000-0003-3565-2482"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Fang","raw_affiliation_strings":["Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, China"],"raw_orcid":"https://orcid.org/0000-0003-3565-2482","affiliations":[{"raw_affiliation_string":"Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014937762","display_name":"Xiang Zhao","orcid":"https://orcid.org/0000-0001-6339-0219"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Zhao","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-6339-0219","affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405121","display_name":"Yifan Chen","orcid":"https://orcid.org/0000-0001-6450-3617"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Chen","raw_affiliation_strings":["Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106942630","display_name":"Weidong Xiao","orcid":"https://orcid.org/0000-0002-6957-3769"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Xiao","raw_affiliation_strings":["Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031439294","display_name":"Maarten de Rijke","orcid":"https://orcid.org/0000-0002-1086-0202"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Maarten de Rijke","raw_affiliation_strings":["University of Amsterdam, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Amsterdam, the Netherlands","institution_ids":["https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5809,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71788904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9947999715805054,"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/T10028","display_name":"Topic Modeling","score":0.982200026512146,"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/computer-science","display_name":"Computer science","score":0.8475018739700317},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5955600738525391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5759598016738892},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5229916572570801},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5122589468955994},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.507824718952179},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5012388229370117},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47954508662223816},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.47250521183013916},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4499446451663971}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8475018739700317},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5955600738525391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5759598016738892},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5229916572570801},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5122589468955994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.507824718952179},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5012388229370117},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47954508662223816},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.47250521183013916},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4499446451663971},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tkde.2022.3206597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3206597","pdf_url":"https://ieeexplore.ieee.org/ielx7/69/4358933/09891783.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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:dare.uva.nl:openaire_cris_publications/9a665ba5-ca7a-4c09-b76a-d2de196696d8","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/pfhin-pretraining-for-heterogeneous-information-networks(9a665ba5-ca7a-4c09-b76a-d2de196696d8).html","pdf_url":"https://pure.uva.nl/ws/files/238845417/PF-HIN.pdf","source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fang, Y, Zhao, X, Chen, Y, Xiao, W & de Rijke, M 2023, 'PF-HIN: Pre-Training for Heterogeneous Information Networks', IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 8, pp. 8372-8385. https://doi.org/10.1109/TKDE.2022.3206597","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:dare.uva.nl:publications/9a665ba5-ca7a-4c09-b76a-d2de196696d8","is_oa":true,"landing_page_url":"https://hdl.handle.net/11245.1/9a665ba5-ca7a-4c09-b76a-d2de196696d8","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fang, Y, Zhao, X, Chen, Y, Xiao, W & de Rijke, M 2023, 'PF-HIN: Pre-Training for Heterogeneous Information Networks', IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 8, pp. 8372-8385. https://doi.org/10.1109/TKDE.2022.3206597","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/tkde.2022.3206597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3206597","pdf_url":"https://ieeexplore.ieee.org/ielx7/69/4358933/09891783.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2605822748","display_name":null,"funder_award_id":"U19B2024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5388974864","display_name":"\u7a00\u758f\u6837\u672c\u6761\u4ef6\u4e0b\u7684\u9886\u57df\u77e5\u8bc6\u56fe\u8c31\u83b7\u53d6\u4e0e\u5229\u7528\u7814\u7a76","funder_award_id":"61872446","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8218347068","display_name":null,"funder_award_id":"62272469","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/F4320321799","display_name":"Ministerie van Onderwijs, Cultuur en Wetenschap","ror":"https://ror.org/02x3w5g21"},{"id":"https://openalex.org/F4320321800","display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","ror":"https://ror.org/04jsz6e67"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4295788917.pdf","grobid_xml":"https://content.openalex.org/works/W4295788917.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W637153065","https://openalex.org/W1662382123","https://openalex.org/W1888005072","https://openalex.org/W2053186076","https://openalex.org/W2087194317","https://openalex.org/W2142535891","https://openalex.org/W2145658888","https://openalex.org/W2154851992","https://openalex.org/W2156718197","https://openalex.org/W2244992438","https://openalex.org/W2393319904","https://openalex.org/W2558460151","https://openalex.org/W2582993595","https://openalex.org/W2743104969","https://openalex.org/W2767774008","https://openalex.org/W2809343047","https://openalex.org/W2809418595","https://openalex.org/W2896457183","https://openalex.org/W2947894439","https://openalex.org/W2952729433","https://openalex.org/W2962711740","https://openalex.org/W2962739339","https://openalex.org/W2962756421","https://openalex.org/W2963017945","https://openalex.org/W2963026768","https://openalex.org/W2963084622","https://openalex.org/W2963224980","https://openalex.org/W2963241951","https://openalex.org/W2964015378","https://openalex.org/W2964145825","https://openalex.org/W2964321699","https://openalex.org/W2965857891","https://openalex.org/W2996428491","https://openalex.org/W3005552578","https://openalex.org/W3012871709","https://openalex.org/W3014996559","https://openalex.org/W3036446966","https://openalex.org/W3042085764","https://openalex.org/W3044410371","https://openalex.org/W3080997787","https://openalex.org/W3099152386","https://openalex.org/W3104097132","https://openalex.org/W3166423611","https://openalex.org/W3172710079","https://openalex.org/W4288275971","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4301040071","https://openalex.org/W6620673361","https://openalex.org/W6637178625","https://openalex.org/W6682755970","https://openalex.org/W6685158001","https://openalex.org/W6713582119","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6732953605","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6749077313","https://openalex.org/W6754929296","https://openalex.org/W6755207826","https://openalex.org/W6763050518","https://openalex.org/W6766156693","https://openalex.org/W6768021236","https://openalex.org/W6772452955","https://openalex.org/W6776140601"],"related_works":["https://openalex.org/W4285146687","https://openalex.org/W2912933387","https://openalex.org/W3013167367","https://openalex.org/W3026084995","https://openalex.org/W2997669297","https://openalex.org/W3087493185","https://openalex.org/W4206762304","https://openalex.org/W2949403962","https://openalex.org/W3208758912","https://openalex.org/W2998930655"],"abstract_inverted_index":{"In":[0,164],"network":[1,27,71],"representation":[2,28,72],"learning":[3,29,73],"we":[4,114,168],"learn":[5],"how":[6],"to":[7,18,37,48,60,77,94,147,160],"represent":[8],"heterogeneous":[9,66],"information":[10,67],"networks":[11],"in":[12],"a":[13,53,65,99,120,124],"low-dimensional":[14],"space":[15],"so":[16],"as":[17],"facilitate":[19],"effective":[20],"search,":[21,178],"classification,":[22,180],"and":[23,56,89,98,110,137,151,156,181],"prediction":[24],"solutions.":[25],"Previous":[26],"methods":[30],"typically":[31],"require":[32],"sufficient":[33],"task-specific":[34,104],"labeled":[35],"data":[36],"address":[38],"domain-specific":[39],"problems.":[40],"The":[41],"trained":[42],"model":[43,81,97,108],"usually":[44],"cannot":[45],"be":[46],"transferred":[47],"out-of-domain":[49],"datasets.":[50,195],"We":[51,141],"propose":[52],"self-supervised":[54,132],"pre-training":[55],"fine-tuning":[57,166],"framework,":[58],"PF-HIN,":[59],"capture":[61],"the":[62,79,96,117,149,162,165],"features":[63],"of":[64,102,119,190],"network.":[68],"Unlike":[69],"traditional":[70],"models":[74],"that":[75],"have":[76],"train":[78,148],"entire":[80],"all":[82],"over":[83],"again":[84],"for":[85],"every":[86],"downstream":[87,172],"task":[88],"dataset,":[90],"PF-HIN":[91,126,184],"only":[92],"needs":[93],"fine-tune":[95],"small":[100],"number":[101],"extra":[103],"parameters,":[105],"thus":[106],"improving":[107],"efficiency":[109],"effectiveness.":[111],"During":[112],"pre-training,":[113],"first":[115],"transform":[116],"neighborhood":[118],"given":[121],"node":[122,135,139,179,182],"into":[123],"sequence.":[125],"is":[127],"pre-trained":[128],"based":[129],"on":[130,188,193],"two":[131],"tasks,":[133,173,192],"masked":[134],"modeling":[136],"adjacent":[138],"prediction.":[140],"adopt":[142],"deep":[143],"bi-directional":[144],"transformer":[145],"encoders":[146],"model,":[150],"leverage":[152],"factorized":[153],"embedding":[154],"parameterization":[155],"cross-layer":[157],"parameter":[158],"sharing":[159],"reduce":[161],"parameters.":[163],"stage,":[167],"choose":[169],"four":[170,194],"benchmark":[171],"i.e.,":[174],"link":[175],"prediction,":[176],"similarity":[177],"clustering.":[183],"outperforms":[185],"state-of-the-art":[186],"alternatives":[187],"each":[189],"these":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}