{"id":"https://openalex.org/W3209967235","doi":"https://doi.org/10.1145/3459637.3482232","title":"Are Negative Samples Necessary in Entity Alignment?","display_name":"Are Negative Samples Necessary in Entity Alignment?","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3209967235","doi":"https://doi.org/10.1145/3459637.3482232","mag":"3209967235"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482232","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102006979","display_name":"Xin Mao","orcid":"https://orcid.org/0000-0001-5991-6708"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Mao","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361565","display_name":"Wenting Wang","orcid":"https://orcid.org/0000-0003-4503-5613"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenting Wang","raw_affiliation_strings":["Alibaba Group, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Singapore, Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118458994","display_name":"Yuanbin Wu","orcid":"https://orcid.org/0009-0009-5670-4940"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanbin Wu","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057508424","display_name":"Man Lan","orcid":"https://orcid.org/0000-0002-1423-1286"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Man Lan","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102006979"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":2.0395,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.89185745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1263","last_page":"1273"},"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/T11719","display_name":"Data Quality and Management","score":0.9970999956130981,"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":0.9944999814033508,"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/scalability","display_name":"Scalability","score":0.8092327117919922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7755903601646423},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7630388140678406},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5754661560058594},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5669316649436951},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5065773725509644},{"id":"https://openalex.org/keywords/dilemma","display_name":"Dilemma","score":0.4567486047744751},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4462781250476837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43988528847694397},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4379671812057495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4357498288154602},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42949387431144714},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36865782737731934},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09160289168357849}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8092327117919922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7755903601646423},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7630388140678406},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5754661560058594},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5669316649436951},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5065773725509644},{"id":"https://openalex.org/C2778496695","wikidata":"https://www.wikidata.org/wiki/Q254128","display_name":"Dilemma","level":2,"score":0.4567486047744751},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4462781250476837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43988528847694397},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4379671812057495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4357498288154602},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42949387431144714},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36865782737731934},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09160289168357849},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482232","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2127795553","https://openalex.org/W2138621090","https://openalex.org/W2171590421","https://openalex.org/W2194775991","https://openalex.org/W2519887557","https://openalex.org/W2551361256","https://openalex.org/W2560674852","https://openalex.org/W2604314403","https://openalex.org/W2617078503","https://openalex.org/W2624431344","https://openalex.org/W2743473392","https://openalex.org/W2746582923","https://openalex.org/W2747329762","https://openalex.org/W2808284704","https://openalex.org/W2890187992","https://openalex.org/W2911778742","https://openalex.org/W2912351665","https://openalex.org/W2945827377","https://openalex.org/W2949700412","https://openalex.org/W2951063632","https://openalex.org/W2953054275","https://openalex.org/W2953122515","https://openalex.org/W2963118869","https://openalex.org/W2963285578","https://openalex.org/W2963858333","https://openalex.org/W2966055354","https://openalex.org/W2970188762","https://openalex.org/W2970921796","https://openalex.org/W2971001654","https://openalex.org/W2994968268","https://openalex.org/W2996919866","https://openalex.org/W2997062749","https://openalex.org/W3001510267","https://openalex.org/W3001896264","https://openalex.org/W3003594370","https://openalex.org/W3005680577","https://openalex.org/W3035524453","https://openalex.org/W3075591326","https://openalex.org/W3080506591","https://openalex.org/W3098583774","https://openalex.org/W3099206234","https://openalex.org/W3101056714","https://openalex.org/W3101553402","https://openalex.org/W3102952580","https://openalex.org/W3107668149","https://openalex.org/W3139164912","https://openalex.org/W3155399633"],"related_works":["https://openalex.org/W4289718052","https://openalex.org/W2164121020","https://openalex.org/W2145559838","https://openalex.org/W2905319430","https://openalex.org/W3116498279","https://openalex.org/W4287549553","https://openalex.org/W4310285384","https://openalex.org/W3183027292","https://openalex.org/W4248896073","https://openalex.org/W2974871044"],"abstract_inverted_index":{"Entity":[0],"alignment":[1,102],"(EA)":[2],"aims":[3],"to":[4,32,42,81,118],"find":[5],"the":[6,120,137],"equivalent":[7],"entities":[8],"in":[9,17,47,64,140],"different":[10],"KGs,":[11],"which":[12],"is":[13],"a":[14,73],"crucial":[15],"step":[16],"integrating":[18],"multiple":[19],"KGs.":[20],"However,":[21],"most":[22],"existing":[23,48],"EA":[24,49,75],"methods":[25],"have":[26],"poor":[27],"scalability":[28,146],"and":[29,60,87,104,122,147],"are":[30],"unable":[31],"cope":[33],"with":[34,77,95],"large-scale":[35],"datasets.":[36],"We":[37],"summarize":[38],"three":[39,78],"issues":[40],"leading":[41],"such":[43],"high":[44,83,85,88],"time-space":[45],"complexity":[46],"methods:":[50],"(1)":[51,91],"Inefficient":[52],"graph":[53,93,97],"encoders,":[54],"(2)":[55,99],"Dilemma":[56],"of":[57,124],"negative":[58],"sampling,":[59,98],"(3)":[61,105],"\"Catastrophic":[62],"forgetting\"":[63],"semi-supervised":[65,107],"learning.":[66,108],"To":[67],"address":[68],"these":[69],"challenges,":[70],"we":[71,110],"propose":[72],"novel":[74],"method":[76],"new":[79],"components":[80],"enable":[82],"Performance,":[84],"Scalability,":[86],"Robustness":[89],"(PSR):":[90],"Simplified":[92],"encoder":[94],"relational":[96],"Symmetric":[100],"negative-free":[101],"loss,":[103],"Incremental":[106],"Furthermore,":[109],"conduct":[111],"detailed":[112],"experiments":[113],"on":[114],"several":[115],"public":[116],"datasets":[117],"examine":[119],"effectiveness":[121],"efficiency":[123],"our":[125],"proposed":[126],"method.":[127],"The":[128],"experimental":[129],"results":[130],"show":[131],"that":[132],"PSR":[133],"not":[134],"only":[135],"surpasses":[136],"previous":[138],"SOTA":[139],"performance":[141],"but":[142],"also":[143],"has":[144],"impressive":[145],"robustness.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}