{"id":"https://openalex.org/W4311107701","doi":"https://doi.org/10.1007/s44230-022-00012-0","title":"A Prototype Network Enhanced Relation Semantic Representation for Few-shot Relation Extraction","display_name":"A Prototype Network Enhanced Relation Semantic Representation for Few-shot Relation Extraction","publication_year":2022,"publication_date":"2022-12-02","ids":{"openalex":"https://openalex.org/W4311107701","doi":"https://doi.org/10.1007/s44230-022-00012-0"},"language":"en","primary_location":{"id":"doi:10.1007/s44230-022-00012-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44230-022-00012-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44230-022-00012-0.pdf","source":{"id":"https://openalex.org/S4210207486","display_name":"Human-Centric Intelligent Systems","issn_l":"2667-1336","issn":["2667-1336"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Human-Centric Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s44230-022-00012-0.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100730977","display_name":"Haitao He","orcid":"https://orcid.org/0000-0001-9338-5605"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haitao He","raw_affiliation_strings":["Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078890183","display_name":"Haoran Niu","orcid":"https://orcid.org/0000-0003-1607-3776"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Niu","raw_affiliation_strings":["Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030911500","display_name":"Jianzhou Feng","orcid":"https://orcid.org/0000-0003-2279-6030"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhou Feng","raw_affiliation_strings":["Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391080","display_name":"Qian Wang","orcid":"https://orcid.org/0000-0002-5906-1890"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Wang","raw_affiliation_strings":["Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088862581","display_name":"Qikai Wei","orcid":"https://orcid.org/0000-0002-1048-3814"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qikai Wei","raw_affiliation_strings":["Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Yanshan University, No. 438, West Section, Hebei Street, Qinhuangdao, 066004, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100730977"],"corresponding_institution_ids":["https://openalex.org/I39333907"],"apc_list":null,"apc_paid":null,"fwci":0.9658,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8001439,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"3","issue":"1","first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9984999895095825,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9728000164031982,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/relation","display_name":"Relation (database)","score":0.7844032049179077},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7750790119171143},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7696599960327148},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.7001224756240845},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6055307388305664},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.549143373966217},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5402891039848328},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5373584032058716},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.484275758266449},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4573880732059479},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.44171440601348877},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37453198432922363},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3583109676837921},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2871156334877014}],"concepts":[{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7844032049179077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7750790119171143},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7696599960327148},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.7001224756240845},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6055307388305664},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.549143373966217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5402891039848328},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5373584032058716},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.484275758266449},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4573880732059479},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.44171440601348877},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37453198432922363},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3583109676837921},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2871156334877014},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44230-022-00012-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44230-022-00012-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44230-022-00012-0.pdf","source":{"id":"https://openalex.org/S4210207486","display_name":"Human-Centric Intelligent Systems","issn_l":"2667-1336","issn":["2667-1336"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Human-Centric Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:660231d3c88140d39b28a383a71e2031","is_oa":true,"landing_page_url":"https://doaj.org/article/660231d3c88140d39b28a383a71e2031","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Human-Centric Intelligent Systems, Vol 3, Iss 1, Pp 1-12 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44230-022-00012-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44230-022-00012-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44230-022-00012-0.pdf","source":{"id":"https://openalex.org/S4210207486","display_name":"Human-Centric Intelligent Systems","issn_l":"2667-1336","issn":["2667-1336"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Human-Centric Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G2456145376","display_name":null,"funder_award_id":"No.204200510002","funder_id":"https://openalex.org/F4320330448","funder_display_name":"Youth and Middle-aged Scientific and Technological Innovation Leading Talents Program of the Corps"}],"funders":[{"id":"https://openalex.org/F4320330448","display_name":"Youth and Middle-aged Scientific and Technological Innovation Leading Talents Program of the Corps","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4311107701.pdf","grobid_xml":"https://content.openalex.org/works/W4311107701.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2107598941","https://openalex.org/W2515462165","https://openalex.org/W2802164284","https://openalex.org/W2905471643","https://openalex.org/W2951615109","https://openalex.org/W2963777632","https://openalex.org/W2971136144","https://openalex.org/W2981647022","https://openalex.org/W2985344461","https://openalex.org/W2987386900","https://openalex.org/W2990230185","https://openalex.org/W3014226836","https://openalex.org/W3034987881","https://openalex.org/W3093861107","https://openalex.org/W3099910226","https://openalex.org/W3114986498","https://openalex.org/W3127427447","https://openalex.org/W3143371164","https://openalex.org/W3144215978","https://openalex.org/W3161557830","https://openalex.org/W3190766156","https://openalex.org/W3194672979","https://openalex.org/W3201556757","https://openalex.org/W3206914626","https://openalex.org/W3209642831","https://openalex.org/W4200308405","https://openalex.org/W4225658837","https://openalex.org/W6629727499"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Abstract":[0],"Few-shot":[1],"relation":[2,21,32,46,61,97,103],"extraction":[3,124],"is":[4,16],"one":[5],"of":[6,41,125,153,166],"the":[7,20,31,39,42,50,92,96,101,108,123,130,136,151,154,164,167],"current":[8],"research":[9,15],"focuses.":[10],"The":[11],"key":[12],"to":[13,17,44,48,69,94,121,133],"this":[14],"fully":[18],"extract":[19,45,70],"semantic":[22,62],"information":[23,84,90],"through":[24,142],"very":[25],"little":[26],"training":[27],"data.":[28],"Intuitively,":[29],"raising":[30],"semantics":[33,98],"awareness":[34],"in":[35,53,91,138],"sentences":[36],"can":[37,162],"improve":[38],"efficiency":[40],"model":[43,64,171],"features":[47,104],"alleviate":[49],"overfitting":[51],"problem":[52],"few-shot":[54,73],"learning.":[55],"Therefore,":[56],"we":[57,76,147],"propose":[58],"an":[59],"enhanced":[60],"feature":[63],"based":[65],"on":[66],"prototype":[67,110],"network":[68],"relations":[71,137],"from":[72],"texts.":[74],"Firstly,":[75],"design":[77],"a":[78,114],"multi-level":[79,156],"embedding":[80,157],"encoder":[81],"with":[82],"position":[83],"and":[85,145,149,159],"Transformer,":[86],"which":[87,112],"uses":[88],"local":[89],"text":[93],"enhance":[95,163],"representation.":[99],"Secondly,":[100],"encoded":[102],"are":[105],"fed":[106],"into":[107],"novel":[109],"network,":[111],"designs":[113],"method":[115],"that":[116],"utilizes":[117],"query":[118,139],"prototype-level":[119,160],"attention":[120,161],"guide":[122],"supporting":[126],"prototypes,":[127],"thereby":[128],"enhancing":[129],"prototypes":[131],"representation":[132],"better":[134],"classify":[135],"sentences.":[140],"Finally,":[141],"experimental":[143],"comparison":[144],"discussion,":[146],"prove":[148],"analyze":[150],"effectiveness":[152],"proposed":[155],"encoder,":[158],"stability":[165],"model.":[168],"Furthermore,":[169],"our":[170],"has":[172],"substantial":[173],"improvements":[174],"over":[175],"baseline":[176],"methods.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-16T09:10:04.655348","created_date":"2025-10-10T00:00:00"}
