{"id":"https://openalex.org/W4205275195","doi":"https://doi.org/10.1109/tnnls.2021.3138956","title":"Interactive Lexical and Semantic Graphs for Semisupervised Relation Extraction","display_name":"Interactive Lexical and Semantic Graphs for Semisupervised Relation Extraction","publication_year":2022,"publication_date":"2022-01-10","ids":{"openalex":"https://openalex.org/W4205275195","doi":"https://doi.org/10.1109/tnnls.2021.3138956","pmid":"https://pubmed.ncbi.nlm.nih.gov/35007203"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3138956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3138956","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100729534","display_name":"Wanli Li","orcid":"https://orcid.org/0000-0003-0670-5397"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanli Li","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-0670-5397","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040759280","display_name":"Tieyun Qian","orcid":"https://orcid.org/0000-0003-4667-5794"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tieyun Qian","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-4667-5794","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033128202","display_name":"Ming Zhong","orcid":"https://orcid.org/0000-0001-9376-818X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhong","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-9376-818X","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100647360","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0003-0003-0210"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":1.7058,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.86082683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"34","issue":"10","first_page":"7158","last_page":"7169"},"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":0.9991999864578247,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9975000023841858,"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":0.7896331548690796},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6862788796424866},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6742392182350159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6286087036132812},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.6145272850990295},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5813701748847961},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5207002758979797},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5067310929298401},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47272223234176636},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4723920524120331},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4511694610118866},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4278217852115631},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4225099980831146},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.34621745347976685},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10811996459960938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896331548690796},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6862788796424866},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6742392182350159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6286087036132812},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.6145272850990295},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5813701748847961},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5207002758979797},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5067310929298401},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47272223234176636},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4723920524120331},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4511694610118866},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4278217852115631},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4225099980831146},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.34621745347976685},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10811996459960938},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3138956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3138956","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35007203","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35007203","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G363500932","display_name":"\u793e\u4f1a\u5a92\u4f53\u4e2d\u7684\u5783\u573e\u7528\u6237\u96c6\u56e2\u8bc6\u522b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61572376","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5675372752","display_name":null,"funder_award_id":"62032016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8770384812","display_name":"\u5173\u952e\u8bcd\u9a71\u52a8\u7684\u7d27\u5bc6\u5b50\u56fe\u67e5\u8be2\u5904\u7406\u6280\u672f\u7814\u7a76","funder_award_id":"61972291","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":49,"referenced_works":["https://openalex.org/W1520377376","https://openalex.org/W2064675550","https://openalex.org/W2079057609","https://openalex.org/W2099779943","https://openalex.org/W2103931177","https://openalex.org/W2116341502","https://openalex.org/W2123442489","https://openalex.org/W2162590473","https://openalex.org/W2187089797","https://openalex.org/W2250539671","https://openalex.org/W2250560707","https://openalex.org/W2251135946","https://openalex.org/W2251622960","https://openalex.org/W2279620300","https://openalex.org/W2517194566","https://openalex.org/W2604610161","https://openalex.org/W2741928062","https://openalex.org/W2759211898","https://openalex.org/W2798393196","https://openalex.org/W2905224888","https://openalex.org/W2911286998","https://openalex.org/W2913964174","https://openalex.org/W2949212908","https://openalex.org/W2950540372","https://openalex.org/W2951345965","https://openalex.org/W2952179106","https://openalex.org/W2952768212","https://openalex.org/W2963014179","https://openalex.org/W2963020213","https://openalex.org/W2963454301","https://openalex.org/W2963655104","https://openalex.org/W2964022985","https://openalex.org/W2964159205","https://openalex.org/W2964165264","https://openalex.org/W2964193968","https://openalex.org/W2996913633","https://openalex.org/W3012687255","https://openalex.org/W3198927718","https://openalex.org/W6639364127","https://openalex.org/W6640267182","https://openalex.org/W6682082992","https://openalex.org/W6726873649","https://openalex.org/W6733814495","https://openalex.org/W6738964360","https://openalex.org/W6739901393","https://openalex.org/W6745537798","https://openalex.org/W6745986955","https://openalex.org/W6757374366","https://openalex.org/W6773088157"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W2444550338","https://openalex.org/W2369351710","https://openalex.org/W2594363579","https://openalex.org/W2169232658"],"abstract_inverted_index":{"The":[0,197],"performance":[1],"of":[2,11,43,65,79,104,108],"relation":[3],"extraction":[4],"(RE)":[5],"is":[6,71,99,176],"hindered":[7],"by":[8,25],"the":[9,31,50,54,59,62,69,74,77,80,102,105,120,127,131,137,146,167,181,186,206],"lack":[10],"sufficient":[12],"labeled":[13,56,81,109,128,152],"data.":[14,33,82,110],"Semisupervised":[15],"methods":[16,38],"can":[17],"offer":[18],"to":[19,73,101,118,142,148,154,164,178],"help":[20],"hands":[21],"with":[22,130,185],"this":[23,84,135],"problem":[24],"augmenting":[26],"high-quality":[27,182],"unlabeled":[28,132,155,183],"samples":[29,129,153,184],"into":[30],"training":[32],"However,":[34],"existing":[35],"semisupervised":[36,90],"RE":[37,91],"either":[39],"need":[40],"a":[41,88,160],"set":[42,107],"manually":[44],"defined":[45],"rules":[46,117],"or":[47],"rely":[48],"on":[49,53,193],"classifier":[51],"trained":[52],"small":[55,95],"data,":[57],"i.e.,":[58],"former":[60],"requires":[61],"heavy":[63],"intervention":[64],"human":[66,96],"knowledge,":[67],"and":[68,76,98,122,172],"latter":[70],"bound":[72],"number":[75],"quality":[78],"In":[83,134],"article,":[85],"we":[86,112],"present":[87],"novel":[89],"method":[92,203],"that":[93,200],"involves":[94],"efforts":[97],"robust":[100],"size":[103],"initial":[106],"Specifically,":[111],"adopt":[113],"only":[114],"two":[115,194],"simple":[116],"build":[119],"lexical":[121,171],"semantic":[123,173],"graphs":[124,138],"which":[125,175],"connect":[126],"ones.":[133,156],"way,":[136],"are":[139],"much":[140],"easier":[141],"construct":[143],"yet":[144],"keep":[145],"ability":[147],"transfer":[149],"knowledge":[150],"from":[151],"We":[157,188],"then":[158],"develop":[159],"graph":[161],"interaction":[162],"module":[163],"fully":[165],"exploit":[166],"reference":[168],"information":[169],"in":[170],"graphs,":[174],"used":[177],"jointly":[179],"recognize":[180],"classifier.":[187],"conduct":[189],"extensive":[190],"experimental":[191],"results":[192,198],"public":[195],"datasets.":[196],"demonstrate":[199],"our":[201],"proposed":[202],"significantly":[204],"outperforms":[205],"state-of-the-art":[207],"baselines.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
