{"id":"https://openalex.org/W4385568189","doi":"https://doi.org/10.1145/3580305.3599397","title":"Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs","display_name":"Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385568189","doi":"https://doi.org/10.1145/3580305.3599397"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5101848528","display_name":"Zequn Sun","orcid":"https://orcid.org/0000-0003-4177-9199"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zequn Sun","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100742563","display_name":"Jiacheng Huang","orcid":"https://orcid.org/0000-0003-1466-7132"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiacheng Huang","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057700970","display_name":"Jinghao Lin","orcid":"https://orcid.org/0000-0002-9067-5946"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghao Lin","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015814459","display_name":"Xiaozhou Xu","orcid":"https://orcid.org/0009-0008-6290-9291"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaozhou Xu","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026513606","display_name":"Qijin Chen","orcid":"https://orcid.org/0000-0002-3252-1383"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qijin Chen","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100727084","display_name":"Wei Hu","orcid":"https://orcid.org/0000-0003-3635-6335"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Hu","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101848528"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08894312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2132","last_page":"2144"},"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/T10028","display_name":"Topic Modeling","score":0.9969000220298767,"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":0.995199978351593,"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":0.7263185381889343},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6972261667251587},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.6050873398780823},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5176197290420532},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.500171422958374},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49808645248413086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4893049895763397},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4719235897064209},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4647839069366455},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.44839373230934143},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.442928284406662},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4369608163833618},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4171411693096161},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3348243236541748},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2637642025947571},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08514079451560974}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7263185381889343},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6972261667251587},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.6050873398780823},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5176197290420532},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.500171422958374},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49808645248413086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4893049895763397},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4719235897064209},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4647839069366455},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.44839373230934143},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.442928284406662},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4369608163833618},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4171411693096161},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3348243236541748},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2637642025947571},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08514079451560974},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3137102087","display_name":null,"funder_award_id":"62272219","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7174558747","display_name":null,"funder_award_id":"Group","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1552847225","https://openalex.org/W2015191210","https://openalex.org/W2064675550","https://openalex.org/W2080133951","https://openalex.org/W2094728533","https://openalex.org/W2107306718","https://openalex.org/W2184957013","https://openalex.org/W2283196293","https://openalex.org/W2521367263","https://openalex.org/W2551361256","https://openalex.org/W2556343638","https://openalex.org/W2560674852","https://openalex.org/W2595002104","https://openalex.org/W2604314403","https://openalex.org/W2728059831","https://openalex.org/W2741609678","https://openalex.org/W2754811377","https://openalex.org/W2759136286","https://openalex.org/W2798980199","https://openalex.org/W2888634710","https://openalex.org/W2890187992","https://openalex.org/W2903963001","https://openalex.org/W2949700412","https://openalex.org/W2953356739","https://openalex.org/W2954996726","https://openalex.org/W2955238243","https://openalex.org/W2962916648","https://openalex.org/W2963359213","https://openalex.org/W2964263523","https://openalex.org/W2964855489","https://openalex.org/W2997062749","https://openalex.org/W3003265726","https://openalex.org/W3011574394","https://openalex.org/W3012000912","https://openalex.org/W3032390337","https://openalex.org/W3034862985","https://openalex.org/W3035134435","https://openalex.org/W3080506591","https://openalex.org/W3082429057","https://openalex.org/W3088409176","https://openalex.org/W3097217077","https://openalex.org/W3098583774","https://openalex.org/W3099384160","https://openalex.org/W3102952580","https://openalex.org/W3116847845","https://openalex.org/W3120491054","https://openalex.org/W3122741928","https://openalex.org/W3142239405","https://openalex.org/W3152740956","https://openalex.org/W3156850293","https://openalex.org/W3175604467","https://openalex.org/W3176770704","https://openalex.org/W4239019441","https://openalex.org/W4287888135","https://openalex.org/W4313159770"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2604454537","https://openalex.org/W2808284704","https://openalex.org/W2897702399","https://openalex.org/W4206028705","https://openalex.org/W2757431232","https://openalex.org/W2954554213","https://openalex.org/W2251363251","https://openalex.org/W4206547516","https://openalex.org/W4293236197"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,71],"present":[4],"the":[5,25,82,86,99,102,144],"\"joint":[6],"pre-training":[7],"and":[8,14,37,52,85,111,130,146],"local":[9],"re-training''":[10],"framework":[11],"for":[12,60,80,94,126],"learning":[13],"applying":[15],"multi-source":[16,50],"knowledge":[17,54,66,96,106,109,113],"graph":[18],"(KG)":[19],"embeddings.":[20,119],"We":[21,40,138],"are":[22],"motivated":[23],"by":[24],"fact":[26],"that":[27],"different":[28,69,127],"KGs":[29,51,84,129],"contain":[30],"complementary":[31],"information":[32],"to":[33,55,75,101,115,134,142],"improve":[34],"KG":[35,45],"embeddings":[36],"downstream":[38],"tasks.":[39],"pre-train":[41],"a":[42,57,61,77],"large":[43],"teacher":[44,100,121],"embedding":[46],"model":[47,59,122],"over":[48],"linked":[49,78,90],"distill":[53],"train":[56,135],"student":[58],"task-specific":[62],"KG.":[63,88],"To":[64],"enable":[65],"transfer":[67],"across":[68],"KGs,":[70],"use":[72],"entity":[73],"alignment":[74],"build":[76],"subgraph":[79,91],"connecting":[81],"pre-trained":[83],"target":[87,128],"The":[89,120],"is":[92],"re-trained":[93],"three-level":[95],"distillation":[97],"from":[98,136],"student,":[103],"i.e.,":[104],"feature":[105],"distillation,":[107,110,114],"network":[108],"prediction":[112],"generate":[116],"more":[117],"expressive":[118],"can":[123],"be":[124],"reused":[125],"tasks":[131],"without":[132],"having":[133],"scratch.":[137],"conduct":[139],"extensive":[140],"experiments":[141],"demonstrate":[143],"effectiveness":[145],"efficiency":[147],"of":[148],"our":[149],"framework.":[150]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}