{"id":"https://openalex.org/W4298616241","doi":"https://doi.org/10.1007/s10618-022-00862-z","title":"Personalised meta-path generation for heterogeneous graph neural networks","display_name":"Personalised meta-path generation for heterogeneous graph neural networks","publication_year":2022,"publication_date":"2022-10-02","ids":{"openalex":"https://openalex.org/W4298616241","doi":"https://doi.org/10.1007/s10618-022-00862-z"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-022-00862-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-022-00862-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-022-00862-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-022-00862-z.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012686016","display_name":"Zhiqiang Zhong","orcid":"https://orcid.org/0000-0002-1226-5597"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhong","raw_affiliation_strings":["Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014600496","display_name":"Cheng\u2013Te Li","orcid":"https://orcid.org/0000-0001-7995-4787"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Cheng-Te Li","raw_affiliation_strings":["Institute of Data Science and the Department of Statistics, National Cheng Kung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Data Science and the Department of Statistics, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073684178","display_name":"Jun Pang","orcid":"https://orcid.org/0000-0002-4521-4112"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":true,"raw_author_name":"Jun Pang","raw_affiliation_strings":["Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg","Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Esch-sur-Alzette, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg","institution_ids":["https://openalex.org/I186903577"]},{"raw_affiliation_string":"Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Esch-sur-Alzette, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014600496","https://openalex.org/A5073684178"],"corresponding_institution_ids":["https://openalex.org/I186903577","https://openalex.org/I91807558"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.1024,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81538057,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"36","issue":"6","first_page":"2299","last_page":"2333"},"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/T10028","display_name":"Topic Modeling","score":0.9955999851226807,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9821000099182129,"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":0.7791298627853394},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5880061388015747},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5710976719856262},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5531203746795654},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.5422961711883545},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5360940098762512},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5137583017349243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.462709903717041},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.42824018001556396},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42082807421684265},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39305463433265686},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3669106960296631},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20244133472442627},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09230300784111023}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7791298627853394},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5880061388015747},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5710976719856262},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5531203746795654},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.5422961711883545},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5360940098762512},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5137583017349243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.462709903717041},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.42824018001556396},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42082807421684265},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39305463433265686},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3669106960296631},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20244133472442627},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09230300784111023},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10618-022-00862-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-022-00862-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-022-00862-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},{"id":"pmh:oai:orbilu.uni.lu:10993/52908","is_oa":true,"landing_page_url":"https://orbilu.uni.lu/handle/10993/52908","pdf_url":null,"source":{"id":"https://openalex.org/S4306401815","display_name":"Open Repository and Bibliography (University of Luxembourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I186903577","host_organization_name":"University of Luxembourg","host_organization_lineage":["https://openalex.org/I186903577"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Mining and Knowledge Discovery, 36 (6), 2299-2333 (2022)","raw_type":"peer reviewed"}],"best_oa_location":{"id":"doi:10.1007/s10618-022-00862-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-022-00862-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-022-00862-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7599999904632568,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G2256031840","display_name":null,"funder_award_id":"109-2636-E-006-017","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G7782279907","display_name":null,"funder_award_id":"108-2218-E-006-036","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320321038","display_name":"Fonds National de la Recherche Luxembourg","ror":"https://ror.org/039z13y21"},{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4298616241.pdf","grobid_xml":"https://content.openalex.org/works/W4298616241.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2033072307","https://openalex.org/W2075010670","https://openalex.org/W2124125910","https://openalex.org/W2145339207","https://openalex.org/W2154851992","https://openalex.org/W2295128594","https://openalex.org/W2604015085","https://openalex.org/W2604314403","https://openalex.org/W2743104969","https://openalex.org/W2767774008","https://openalex.org/W2775482448","https://openalex.org/W2808927717","https://openalex.org/W2896161497","https://openalex.org/W2911286998","https://openalex.org/W2913312729","https://openalex.org/W2963707260","https://openalex.org/W2965857891","https://openalex.org/W2996910652","https://openalex.org/W3004507689","https://openalex.org/W3012871709","https://openalex.org/W3022514719","https://openalex.org/W3033378605","https://openalex.org/W3035719901","https://openalex.org/W3042085764","https://openalex.org/W3091502028","https://openalex.org/W3094411093","https://openalex.org/W3100789280","https://openalex.org/W3101049536","https://openalex.org/W3103513278","https://openalex.org/W3104097132","https://openalex.org/W3165913101","https://openalex.org/W4214717370","https://openalex.org/W4293249558"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W2988126442","https://openalex.org/W187740018","https://openalex.org/W2162286586","https://openalex.org/W4255368532","https://openalex.org/W3206937279","https://openalex.org/W4360604087"],"abstract_inverted_index":{"Abstract":[0],"Recently,":[1],"increasing":[2],"attention":[3],"has":[4],"been":[5],"paid":[6],"to":[7,15,52,70,80,104,146,187],"heterogeneous":[8,23],"graph":[9],"representation":[10],"learning":[11,169],"(HGRL),":[12],"which":[13,49],"aims":[14],"embed":[16],"rich":[17],"structural":[18],"and":[19,118,141,155,192,206,211,217],"semantic":[20],"information":[21,24],"in":[22,115,220],"networks":[25],"(HINs)":[26],"into":[27],"low-dimensional":[28],"node":[29,72,75,114,120,128,154,159,224],"representations.":[30,160],"To":[31,84],"date,":[32],"most":[33],"HGRL":[34,67],"models":[35],"rely":[36],"on":[37,43,175],"hand-crafted":[38],"meta-paths.":[39],"However,":[40],"the":[41,59,87,123,133,172,194,197],"dependency":[42],"manually-defined":[44],"meta-paths":[45,63,107,236],"requires":[46],"domain":[47],"knowledge,":[48],"is":[50,164],"difficult":[51],"obtain":[53],"for":[54,111,122,151],"complex":[55],"HINs.":[56],"More":[57],"importantly,":[58],"pre-defined":[60],"or":[61,74],"generated":[62],"of":[64,89,223],"all":[65],"existing":[66],"methods":[68,219],"attached":[69],"each":[71,81,112,152],"type":[73],"pair":[76],"cannot":[77],"be":[78],"personalised":[79,110],"individual":[82,113,153],"node.":[83],"fully":[85],"unleash":[86],"power":[88],"HGRL,":[90],"we":[91],"present":[92],"a":[93,116,137,143,149,176],"novel":[94],"framework,":[95],"Personalised":[96],"Meta-path":[97],"based":[98],"Heterogeneous":[99],"Graph":[100],"Neural":[101],"Networks":[102],"(PM-HGNN),":[103],"jointly":[105],"generate":[106,148],"that":[108,203,230],"are":[109],"HIN":[117],"learn":[119,157],"representations":[121],"target":[124],"downstream":[125,177],"task":[126],"like":[127],"classification.":[129,225],"Precisely,":[130],"PM-HGNN":[131,184,205,207,231],"treats":[132],"meta-path":[134,150,198],"generation":[135],"as":[136],"Markov":[138],"Decision":[139],"Process":[140],"utilises":[142],"policy":[144,162],"network":[145,163],"adaptively":[147],"simultaneously":[156],"effective":[158],"The":[161],"trained":[165],"with":[166],"deep":[167],"reinforcement":[168],"by":[170,238],"exploiting":[171],"performance":[173],"improvement":[174],"task.":[178],"We":[179],"further":[180],"propose":[181],"an":[182],"extension,":[183],"++":[185,208,232],",":[186],"better":[188],"encode":[189],"relational":[190],"structure":[191],"accelerate":[193],"training":[195],"during":[196],"generation.":[199],"Experimental":[200],"results":[201],"reveal":[202],"both":[204],"can":[209,233],"significantly":[210],"consistently":[212],"outperform":[213],"16":[214],"competing":[215],"baselines":[216],"state-of-the-art":[218],"various":[221],"settings":[222],"Qualitative":[226],"analysis":[227],"also":[228],"shows":[229],"identify":[234],"meaningful":[235],"overlooked":[237],"human":[239],"knowledge.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
