{"id":"https://openalex.org/W4389146766","doi":"https://doi.org/10.1007/s11280-023-01221-8","title":"Entity alignment via graph neural networks: a component-level study","display_name":"Entity alignment via graph neural networks: a component-level study","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4389146766","doi":"https://doi.org/10.1007/s11280-023-01221-8"},"language":"en","primary_location":{"id":"doi:10.1007/s11280-023-01221-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11280-023-01221-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11280-023-01221-8.pdf","source":{"id":"https://openalex.org/S129236917","display_name":"World Wide Web","issn_l":"1386-145X","issn":["1386-145X","1573-1413"],"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":"World Wide Web","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/s11280-023-01221-8.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070864647","display_name":"Yanfeng Shu","orcid":null},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"funder","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Yanfeng Shu","raw_affiliation_strings":["Data61, CSIRO, Hobart, Australia"],"affiliations":[{"raw_affiliation_string":"Data61, CSIRO, Hobart, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101787171","display_name":"Ji Zhang","orcid":"https://orcid.org/0000-0001-6141-239X"},"institutions":[{"id":"https://openalex.org/I185523456","display_name":"University of Southern Queensland","ror":"https://ror.org/04sjbnx57","country_code":"AU","type":"education","lineage":["https://openalex.org/I185523456"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ji Zhang","raw_affiliation_strings":["University of Southern Queensland, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"University of Southern Queensland, Brisbane, Australia","institution_ids":["https://openalex.org/I185523456"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066831688","display_name":"Guangyan Huang","orcid":"https://orcid.org/0000-0002-1821-8644"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guangyan Huang","raw_affiliation_strings":["Deakin University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Deakin University, Melbourne, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058644115","display_name":"Chi\u2010Hung Chi","orcid":"https://orcid.org/0000-0001-7271-1926"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chi-Hung Chi","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101016518","display_name":"Jing He","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]},{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jing He","raw_affiliation_strings":["Oxford University, Oxford, England"],"affiliations":[{"raw_affiliation_string":"Oxford University, Oxford, England","institution_ids":["https://openalex.org/I4210146410","https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070864647"],"corresponding_institution_ids":["https://openalex.org/I1292875679","https://openalex.org/I42894916"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.5634,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86793322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"26","issue":"6","first_page":"4069","last_page":"4092"},"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/T11719","display_name":"Data Quality and Management","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9968000054359436,"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":0.8819383382797241},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5677140355110168},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5665090084075928},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.565377950668335},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5373223423957825},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5343842506408691},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5207598209381104},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41284430027008057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4013745188713074},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23835813999176025}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8819383382797241},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5677140355110168},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5665090084075928},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.565377950668335},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5373223423957825},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5343842506408691},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5207598209381104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41284430027008057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4013745188713074},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23835813999176025},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11280-023-01221-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11280-023-01221-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11280-023-01221-8.pdf","source":{"id":"https://openalex.org/S129236917","display_name":"World Wide Web","issn_l":"1386-145X","issn":["1386-145X","1573-1413"],"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":"World Wide Web","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/24817689","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Entity_alignment_via_graph_neural_networks_a_component-level_study/24817689","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s11280-023-01221-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11280-023-01221-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11280-023-01221-8.pdf","source":{"id":"https://openalex.org/S129236917","display_name":"World Wide Web","issn_l":"1386-145X","issn":["1386-145X","1573-1413"],"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":"World Wide Web","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320386","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4389146766.pdf"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W102708294","https://openalex.org/W1536929369","https://openalex.org/W1597082186","https://openalex.org/W2007682403","https://openalex.org/W2013093146","https://openalex.org/W2022166150","https://openalex.org/W2031250218","https://openalex.org/W2064675550","https://openalex.org/W2086937365","https://openalex.org/W2116341502","https://openalex.org/W2118100588","https://openalex.org/W2493916176","https://openalex.org/W2522744581","https://openalex.org/W2551361256","https://openalex.org/W2612773933","https://openalex.org/W2741750617","https://openalex.org/W2808284704","https://openalex.org/W2890187992","https://openalex.org/W2891896107","https://openalex.org/W2907492528","https://openalex.org/W2949700412","https://openalex.org/W2953054275","https://openalex.org/W2955238243","https://openalex.org/W2962810718","https://openalex.org/W2962916648","https://openalex.org/W2963691861","https://openalex.org/W2966720878","https://openalex.org/W2970188762","https://openalex.org/W2970921796","https://openalex.org/W2971001654","https://openalex.org/W2980525481","https://openalex.org/W2980563481","https://openalex.org/W2986711944","https://openalex.org/W2997062749","https://openalex.org/W2998390358","https://openalex.org/W3001896264","https://openalex.org/W3030216914","https://openalex.org/W3034303554","https://openalex.org/W3034906292","https://openalex.org/W3075591326","https://openalex.org/W3089874281","https://openalex.org/W3093988619","https://openalex.org/W3098038527","https://openalex.org/W3098583774","https://openalex.org/W3101056714","https://openalex.org/W3111851097","https://openalex.org/W3117053671","https://openalex.org/W3122031757","https://openalex.org/W3146701396","https://openalex.org/W3152893301","https://openalex.org/W3155355417","https://openalex.org/W3155638005","https://openalex.org/W3156850293","https://openalex.org/W3156859417","https://openalex.org/W3161248896","https://openalex.org/W4224309032","https://openalex.org/W4289533781","https://openalex.org/W4306317022","https://openalex.org/W6605946209"],"related_works":["https://openalex.org/W2604454537","https://openalex.org/W4206028705","https://openalex.org/W2808284704","https://openalex.org/W2883748392","https://openalex.org/W2897702399","https://openalex.org/W2757431232","https://openalex.org/W2954554213","https://openalex.org/W3200431764","https://openalex.org/W4288286922","https://openalex.org/W4206547516"],"abstract_inverted_index":{"Abstract":[0],"Entity":[1],"alignment":[2,111,133,145,161],"plays":[3],"an":[4],"essential":[5],"role":[6],"in":[7,46,71],"the":[8,23,66,92,114,144],"integration":[9],"of":[10,68,94,117,125],"knowledge":[11],"graphs":[12],"(KGs)":[13],"as":[14],"it":[15],"seeks":[16],"to":[17,22,52,55,86],"identify":[18],"entities":[19],"that":[20,112,141],"refer":[21],"same":[24],"real-world":[25],"objects":[26],"across":[27],"different":[28],"KGs.":[29,64],"Recent":[30],"research":[31],"has":[32],"primarily":[33],"centred":[34],"on":[35,132],"embedding-based":[36],"approaches.":[37,82,119],"Among":[38],"these":[39,101,118],"approaches,":[40],"there":[41],"is":[42],"a":[43,106,122],"growing":[44],"interest":[45],"graph":[47],"neural":[48],"networks":[49,157],"(GNNs)":[50],"due":[51],"their":[53,130],"ability":[54],"capture":[56],"complex":[57],"relationships":[58],"and":[59,97,128],"incorporate":[60],"node":[61],"attributes":[62],"within":[63],"Despite":[65],"presence":[67],"several":[69],"surveys":[70],"this":[72,103],"area,":[73],"they":[74,84],"often":[75],"lack":[76],"comprehensive":[77],"investigations":[78],"specifically":[79],"targeting":[80],"GNN-based":[81,109],"Moreover,":[83],"tend":[85],"evaluate":[87],"overall":[88],"performance":[89],"without":[90],"analysing":[91],"impact":[93],"individual":[95,126],"components":[96,127],"methods.":[98],"To":[99],"bridge":[100],"gaps,":[102],"paper":[104],"presents":[105],"framework":[107],"for":[108,152],"entity":[110],"captures":[113],"key":[115],"characteristics":[116],"We":[120],"conduct":[121],"fine-grained":[123],"analysis":[124],"assess":[129],"influences":[131],"results.":[134,162],"Our":[135],"findings":[136],"highlight":[137],"specific":[138],"module":[139],"options":[140],"significantly":[142],"affect":[143],"outcomes.":[146],"By":[147],"carefully":[148],"selecting":[149],"suitable":[150],"methods":[151],"combination,":[153],"even":[154],"basic":[155],"GNN":[156],"can":[158],"achieve":[159],"competitive":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
