{"id":"https://openalex.org/W4386863976","doi":"https://doi.org/10.3390/sym15091788","title":"Distantly Supervised Relation Extraction via Contextual Information Interaction and Relation Embeddings","display_name":"Distantly Supervised Relation Extraction via Contextual Information Interaction and Relation Embeddings","publication_year":2023,"publication_date":"2023-09-18","ids":{"openalex":"https://openalex.org/W4386863976","doi":"https://doi.org/10.3390/sym15091788"},"language":"en","primary_location":{"id":"doi:10.3390/sym15091788","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15091788","pdf_url":"https://www.mdpi.com/2073-8994/15/9/1788/pdf?version=1695103092","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/15/9/1788/pdf?version=1695103092","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101314038","display_name":"Huixin Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huixin Yin","raw_affiliation_strings":["College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025798843","display_name":"Shengquan Liu","orcid":"https://orcid.org/0000-0001-9623-4714"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shengquan Liu","raw_affiliation_strings":["College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"],"raw_orcid":"https://orcid.org/0000-0001-9623-4714","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008748688","display_name":"Zhaorui Jian","orcid":"https://orcid.org/0009-0002-7025-9950"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaorui Jian","raw_affiliation_strings":["College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"],"raw_orcid":"https://orcid.org/0009-0002-7025-9950","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025798843"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.674,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7573974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"15","issue":"9","first_page":"1788","last_page":"1788"},"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":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","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"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.8349999189376831},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.7870761156082153},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7710668444633484},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6137430667877197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.598030686378479},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5455564260482788},{"id":"https://openalex.org/keywords/interaction-information","display_name":"Interaction information","score":0.4375472366809845},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43190380930900574},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4223717749118805},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4215671718120575},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.39831024408340454},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36223676800727844},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34509795904159546},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1592746078968048}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8349999189376831},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.7870761156082153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7710668444633484},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6137430667877197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.598030686378479},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5455564260482788},{"id":"https://openalex.org/C38764148","wikidata":"https://www.wikidata.org/wiki/Q17098245","display_name":"Interaction information","level":2,"score":0.4375472366809845},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43190380930900574},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4223717749118805},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4215671718120575},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.39831024408340454},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36223676800727844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34509795904159546},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1592746078968048},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/sym15091788","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15091788","pdf_url":"https://www.mdpi.com/2073-8994/15/9/1788/pdf?version=1695103092","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ef912e30751b4fed94b91544756ea640","is_oa":false,"landing_page_url":"https://doaj.org/article/ef912e30751b4fed94b91544756ea640","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 15, Iss 9, p 1788 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/sym15091788","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15091788","pdf_url":"https://www.mdpi.com/2073-8994/15/9/1788/pdf?version=1695103092","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G6967985870","display_name":null,"funder_award_id":"61966034","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":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386863976.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W174427690","https://openalex.org/W1604644367","https://openalex.org/W2030924903","https://openalex.org/W2107598941","https://openalex.org/W2120814856","https://openalex.org/W2127795553","https://openalex.org/W2132679783","https://openalex.org/W2146304342","https://openalex.org/W2148721079","https://openalex.org/W2162391686","https://openalex.org/W2162590473","https://openalex.org/W2251135946","https://openalex.org/W2251315883","https://openalex.org/W2515462165","https://openalex.org/W2517194566","https://openalex.org/W2891417293","https://openalex.org/W2892316911","https://openalex.org/W2908559012","https://openalex.org/W2945260553","https://openalex.org/W2950813464","https://openalex.org/W2952402849","https://openalex.org/W2962784628","https://openalex.org/W2963021258","https://openalex.org/W2963653592","https://openalex.org/W2963655104","https://openalex.org/W2964167098","https://openalex.org/W2964173876","https://openalex.org/W2970218469","https://openalex.org/W2970288995","https://openalex.org/W3064097317","https://openalex.org/W3115921524","https://openalex.org/W3153655254","https://openalex.org/W3189241502","https://openalex.org/W3208624098","https://openalex.org/W3214342214","https://openalex.org/W4206693003","https://openalex.org/W6682137061","https://openalex.org/W6683883671"],"related_works":["https://openalex.org/W3120400911","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/W2169232658","https://openalex.org/W2369351710"],"abstract_inverted_index":{"Distantly":[0],"supervised":[1],"relation":[2,31,66,90,144,150],"extraction":[3],"(DSRE)":[4],"utilizes":[5],"an":[6],"external":[7],"knowledge":[8],"base":[9],"to":[10,18,27,33,100,106,147,165],"automatically":[11],"label":[12],"a":[13,35,50,102],"corpus,":[14],"which":[15,161],"inevitably":[16],"leads":[17],"the":[19,42,46,58,65,85,118,123,128,133,143,149,159,163,167,172,186,191,197],"problem":[20],"of":[21,38,53,61,122,174],"mislabeling.":[22],"Existing":[23],"approaches":[24],"utilize":[25,96],"BERT":[26,97],"provide":[28],"instances":[29],"and":[30,40,69,89,98,113,139,189],"embeddings":[32,67,91,145,151],"capture":[34],"wide":[36],"set":[37],"relations":[39],"address":[41],"noise":[43,168],"problem.":[44],"However,":[45],"method":[47,52,183,188],"suffers":[48],"from":[49],"single":[51],"textual":[54],"information":[55,60,87,109,116],"processing,":[56],"underutilizing":[57],"feature":[59],"entity":[62,137,140],"pairs":[63,138,141],"in":[64,142],"part":[68],"being":[70],"interfered":[71],"with":[72],"by":[73,111,170,194],"noisy":[74],"labels":[75],"when":[76],"classifying":[77],"multiple":[78],"labels.":[79],"For":[80],"this":[81],"reason,":[82],"we":[83,95,131,154],"propose":[84],"contextual":[86,108],"interaction":[88,110],"(CIRE)":[92],"method.":[93],"First,":[94],"Bi-LSTM":[99,124],"construct":[101],"neural":[103],"network":[104],"model":[105],"enhance":[107],"filtering":[112],"supplementing":[114],"sequence":[115],"through":[117],"error":[119],"repair":[120],"capability":[121],"gating":[125],"mechanism.":[126],"At":[127],"same":[129],"time,":[130],"combine":[132],"vector":[134],"difference":[135],"between":[136],"layer":[146],"improve":[148],"accuracy.":[152],"Finally,":[153],"choose":[155],"sparse":[156],"softmax":[157],"as":[158],"classifier,":[160],"improves":[162,190],"ability":[164],"control":[166],"categories":[169],"controlling":[171],"number":[173],"output":[175],"categories.":[176],"The":[177],"experimental":[178],"results":[179],"show":[180],"that":[181],"our":[182],"significantly":[184],"outperforms":[185],"baseline":[187],"AUC":[192],"metric":[193],"2.6%":[195],"on":[196],"NYT2010":[198],"dataset.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}