{"id":"https://openalex.org/W4412377867","doi":"https://doi.org/10.1145/3726302.3730247","title":"RSGEA: Relationship Structure Line Graph for Semi-supervised Entity Alignment based on Edge Weight Adjustment","display_name":"RSGEA: Relationship Structure Line Graph for Semi-supervised Entity Alignment based on Edge Weight Adjustment","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412377867","doi":"https://doi.org/10.1145/3726302.3730247"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3730247","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730247","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730247","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730247","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053261202","display_name":"Linlin Ding","orcid":"https://orcid.org/0000-0002-4524-1647"},"institutions":[{"id":"https://openalex.org/I118803816","display_name":"Liaoning University","ror":"https://ror.org/03xpwj629","country_code":"CN","type":"education","lineage":["https://openalex.org/I118803816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlin Ding","raw_affiliation_strings":["School of Information, Liaoning University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-4524-1647","affiliations":[{"raw_affiliation_string":"School of Information, Liaoning University, Shenyang, China","institution_ids":["https://openalex.org/I118803816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113496277","display_name":"M. Si","orcid":null},"institutions":[{"id":"https://openalex.org/I118803816","display_name":"Liaoning University","ror":"https://ror.org/03xpwj629","country_code":"CN","type":"education","lineage":["https://openalex.org/I118803816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengjunyao Si","raw_affiliation_strings":["School of Information, Liaoning University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0006-9619-8171","affiliations":[{"raw_affiliation_string":"School of Information, Liaoning University, Shenyang, China","institution_ids":["https://openalex.org/I118803816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100361464","display_name":"Mo Li","orcid":"https://orcid.org/0000-0002-8943-0191"},"institutions":[{"id":"https://openalex.org/I118803816","display_name":"Liaoning University","ror":"https://ror.org/03xpwj629","country_code":"CN","type":"education","lineage":["https://openalex.org/I118803816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mo Li","raw_affiliation_strings":["School of Information, Liaoning University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-8943-0191","affiliations":[{"raw_affiliation_string":"School of Information, Liaoning University, Shenyang, China","institution_ids":["https://openalex.org/I118803816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I118803816"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.120296,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3070","last_page":"3074"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9990000128746033,"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":0.9952999949455261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.621039628982544},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5816317200660706},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5447760820388794},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4996790885925293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4722321033477783},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.42928194999694824},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.416443407535553},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35741618275642395},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23119935393333435},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2120072841644287},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08379942178726196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.621039628982544},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5816317200660706},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5447760820388794},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4996790885925293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4722321033477783},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.42928194999694824},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.416443407535553},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35741618275642395},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23119935393333435},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2120072841644287},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08379942178726196}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3726302.3730247","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730247","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730247","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3726302.3730247","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730247","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730247","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2214187659","display_name":null,"funder_award_id":"No.2022-KF-13-06, 2022-BS-111","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G2292184368","display_name":null,"funder_award_id":"2022-BS-111","funder_id":"https://openalex.org/F4320323086","funder_display_name":"Natural Science Foundation of Liaoning Province"},{"id":"https://openalex.org/G4477924339","display_name":null,"funder_award_id":"62072220","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6224804501","display_name":null,"funder_award_id":"62072220","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G7627306223","display_name":null,"funder_award_id":"2022-KF-13-06","funder_id":"https://openalex.org/F4320323086","funder_display_name":"Natural Science Foundation of Liaoning Province"},{"id":"https://openalex.org/G8418227350","display_name":null,"funder_award_id":"2022YFC3004603","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320323086","display_name":"Natural Science Foundation of Liaoning Province","ror":null},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320324783","display_name":"Liaoning University","ror":"https://ror.org/03xpwj629"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412377867.pdf","grobid_xml":"https://content.openalex.org/works/W4412377867.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1552847225","https://openalex.org/W2022166150","https://openalex.org/W2551361256","https://openalex.org/W2739965732","https://openalex.org/W2741750617","https://openalex.org/W2746582923","https://openalex.org/W2808284704","https://openalex.org/W2890187992","https://openalex.org/W2908230750","https://openalex.org/W2949700412","https://openalex.org/W2962916648","https://openalex.org/W2997062749","https://openalex.org/W3035191547","https://openalex.org/W3089874281","https://openalex.org/W3098583774","https://openalex.org/W3111851097","https://openalex.org/W3214433768","https://openalex.org/W4289533781","https://openalex.org/W4291012579","https://openalex.org/W4385574247","https://openalex.org/W4387171240","https://openalex.org/W4390381374","https://openalex.org/W4390393145","https://openalex.org/W4399152810","https://openalex.org/W4402177625","https://openalex.org/W6755441456"],"related_works":["https://openalex.org/W2052899165","https://openalex.org/W2008562718","https://openalex.org/W1495971547","https://openalex.org/W2067604523","https://openalex.org/W2602089430","https://openalex.org/W2065616796","https://openalex.org/W4400122416","https://openalex.org/W2905809152","https://openalex.org/W3017987646","https://openalex.org/W153309283"],"abstract_inverted_index":{"Entity":[0,59],"alignment":[1,122],"(EA)":[2],"aims":[3],"to":[4,25,33,96,116,130],"identify":[5],"equivalent":[6],"entities":[7],"across":[8],"different":[9],"knowledge":[10],"graphs":[11],"(KGs).":[12],"While":[13],"existing":[14],"approaches":[15],"leverage":[16],"KG":[17],"neighborhood":[18],"structures":[19,78],"for":[20,57],"alignment,":[21],"they":[22],"often":[23],"fail":[24],"effectively":[26],"distinguish":[27],"relevant":[28],"from":[29,85],"irrelevant":[30],"neighbors":[31],"due":[32],"insufficient":[34],"handling":[35],"of":[36,104,145],"neighbor":[37],"heterogeneity.":[38],"Additionally,":[39],"entity":[40,71],"enhancement":[41],"strategies":[42],"remain":[43],"underutilized.":[44],"To":[45],"address":[46],"these":[47],"issues,":[48],"we":[49,111,125],"propose":[50],"a":[51],"novel":[52],"Relationship":[53],"Structure":[54],"Line":[55],"Graph":[56],"Semi-supervised":[58],"Alignment":[60],"Based":[61],"on":[62,136],"Edge":[63],"Weight":[64],"Adjustment,":[65],"named":[66],"RSGEA.":[67],"It":[68,90],"first":[69],"enhances":[70],"representations":[72],"by":[73],"deeply":[74],"analyzing":[75],"relational":[76,83],"connectivity":[77],"in":[79],"KGs,":[80],"capturing":[81],"key":[82],"information":[84,108],"second-order":[86],"and":[87,143],"triangular-ring":[88],"structures.":[89],"then":[91],"employs":[92],"an":[93,127],"attention":[94],"mechanism":[95],"dynamically":[97],"adjust":[98],"edge":[99],"weights,":[100],"mitigating":[101],"the":[102,113,118,141,146],"impact":[103],"noisy":[105],"edges":[106],"during":[107],"propagation.":[109],"Finally,":[110],"employ":[112],"Sinkhorn":[114],"algorithm":[115],"refine":[117],"similarity":[119],"matrix,":[120],"improving":[121],"accuracy.":[123],"Furthermore,":[124],"introduce":[126],"unsupervised":[128],"version":[129],"accommodate":[131],"diverse":[132],"scenarios.":[133],"Extensive":[134],"experiments":[135],"five":[137],"cross-lingual":[138],"datasets":[139],"validate":[140],"effectiveness":[142],"robustness":[144],"RSGEA,":[147],"demonstrating":[148],"significant":[149],"performance":[150],"improvements.":[151]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}