{"id":"https://openalex.org/W2941916520","doi":"https://doi.org/10.1109/access.2019.2913316","title":"MSnet: Multi-Head Self-Attention Network for Distantly Supervised Relation Extraction","display_name":"MSnet: Multi-Head Self-Attention Network for Distantly Supervised Relation Extraction","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2941916520","doi":"https://doi.org/10.1109/access.2019.2913316","mag":"2941916520"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2913316","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2913316","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08698900.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08698900.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102795757","display_name":"Tingting Sun","orcid":"https://orcid.org/0000-0002-7383-1847"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingting Sun","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7383-1847","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100633263","display_name":"Chunhong Zhang","orcid":"https://orcid.org/0000-0003-3008-1887"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhong Zhang","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028862897","display_name":"Yang Ji","orcid":"https://orcid.org/0000-0002-4315-761X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Ji","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075198788","display_name":"Zheng Hu","orcid":"https://orcid.org/0000-0002-8874-5466"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Hu","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.8471,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.79798947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"54472","last_page":"54482"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9937000274658203,"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":0.7307359576225281},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.5495107769966125},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5439683198928833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5188387632369995},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.47848671674728394},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.4414190351963043},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41456273198127747},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3559224605560303},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2799384593963623},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.10123085975646973},{"id":"https://openalex.org/keywords/paleontology","display_name":"Paleontology","score":0.0890180766582489},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.08772367238998413}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7307359576225281},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.5495107769966125},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5439683198928833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5188387632369995},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.47848671674728394},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4414190351963043},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41456273198127747},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3559224605560303},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2799384593963623},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10123085975646973},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0890180766582489},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08772367238998413},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2913316","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2913316","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08698900.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:39d8125c744b4cc0a4a1ce028960fec9","is_oa":true,"landing_page_url":"https://doaj.org/article/39d8125c744b4cc0a4a1ce028960fec9","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 54472-54482 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2913316","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2913316","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08698900.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G2873309782","display_name":null,"funder_award_id":"61421061","funder_id":"https://openalex.org/F4320321470","funder_display_name":"Beijing University of Posts and Telecommunications"},{"id":"https://openalex.org/G462290852","display_name":null,"funder_award_id":"61602048","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5814277799","display_name":null,"funder_award_id":"61520106007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G731386166","display_name":null,"funder_award_id":"61601046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7525308630","display_name":null,"funder_award_id":"61421061","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"},{"id":"https://openalex.org/F4320321470","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2941916520.pdf","grobid_xml":"https://content.openalex.org/works/W2941916520.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W174427690","https://openalex.org/W1491975949","https://openalex.org/W1522301498","https://openalex.org/W1604644367","https://openalex.org/W1832693441","https://openalex.org/W2095705004","https://openalex.org/W2104411075","https://openalex.org/W2107598941","https://openalex.org/W2132679783","https://openalex.org/W2132984949","https://openalex.org/W2141599568","https://openalex.org/W2194775991","https://openalex.org/W2250521169","https://openalex.org/W2250539671","https://openalex.org/W2251135946","https://openalex.org/W2256388387","https://openalex.org/W2296073425","https://openalex.org/W2415204069","https://openalex.org/W2515462165","https://openalex.org/W2597655663","https://openalex.org/W2604610161","https://openalex.org/W2606901057","https://openalex.org/W2759996146","https://openalex.org/W2760600531","https://openalex.org/W2788031953","https://openalex.org/W2896457183","https://openalex.org/W2901004874","https://openalex.org/W2951274974","https://openalex.org/W2952230511","https://openalex.org/W2962924839","https://openalex.org/W2962939608","https://openalex.org/W2963560594","https://openalex.org/W2964317478","https://openalex.org/W3100445485","https://openalex.org/W4385245566","https://openalex.org/W6607091552","https://openalex.org/W6629386296","https://openalex.org/W6636320352","https://openalex.org/W6674330103","https://openalex.org/W6679390333","https://openalex.org/W6679781796","https://openalex.org/W6680890276","https://openalex.org/W6683738474","https://openalex.org/W6691723933","https://openalex.org/W6691895530","https://openalex.org/W6735888106","https://openalex.org/W6739901393","https://openalex.org/W6746565888","https://openalex.org/W6746856007","https://openalex.org/W6748277835","https://openalex.org/W6750643721"],"related_works":["https://openalex.org/W2976808399","https://openalex.org/W2609844752","https://openalex.org/W2981341912","https://openalex.org/W4285246823","https://openalex.org/W4226278302","https://openalex.org/W4221160509","https://openalex.org/W2547211086","https://openalex.org/W2538200646","https://openalex.org/W1968988659","https://openalex.org/W2888033806"],"abstract_inverted_index":{"Distant":[0],"supervision":[1],"for":[2,48,70],"relation":[3,71,170],"extraction":[4],"is":[5,140],"a":[6,15,62,88,109,126,152,213],"task":[7],"of":[8,18,108,155,168,177,192],"recognizing":[9],"semantic":[10],"relations":[11],"between":[12,115],"entities":[13,79],"in":[14,196],"large":[16],"amount":[17],"plain":[19],"text":[20],"weakly":[21],"supervised":[22],"by":[23,143],"external":[24],"knowledge":[25,35],"bases,":[26],"which":[27,180],"can":[28,103,221],"benefit":[29],"many":[30],"NLP":[31],"applications,":[32],"such":[33],"as":[34,147,212],"graph":[36],"completion":[37],"and":[38,80,111],"question":[39],"answering.":[40],"While":[41],"it":[42,51],"significantly":[43],"alleviates":[44],"the":[45,77,94,105,113,134,148,164,190,199,207,223,227],"expensive":[46],"cost":[47],"data":[49],"labeling,":[50],"severely":[52],"suffers":[53],"from":[54],"noisy":[55,135],"labels.":[56,136],"In":[57],"this":[58],"paper,":[59],"we":[60,75,124,204],"propose":[61],"Multi-head":[63],"Self-attention":[64],"Network":[65],"(MSNet)-based":[66],"label":[67,128,139,156,159,167,175,183],"denoising":[68,160],"method":[69,131],"extraction.":[72],"More":[73],"specifically,":[74],"encode":[76],"words,":[78],"their":[81,121],"positions":[82],"information":[83],"into":[84,172],"contextual":[85],"embeddings":[86],"via":[87],"multi-head":[89],"self-attention":[90],"mechanism,":[91],"then":[92],"extract":[93],"discriminative":[95],"sentence":[96,110],"features":[97],"with":[98],"max":[99],"pooling":[100],"operation.":[101],"MSNet":[102],"capture":[104],"inherent":[106],"structure":[107],"model":[112,211],"relatedness":[114],"two":[116],"words":[117],"without":[118],"regard":[119],"to":[120,132,151,198],"distance.":[122],"Moreover,":[123],"adopt":[125],"novel":[127],"confidence":[129],"learning":[130,185],"correct":[133],"A":[137],"latent":[138,166,174,182],"predicted":[141],"step":[142,144],"during":[145],"training":[146],"ground-truth":[149],"according":[150],"curriculum":[153],"function":[154],"confidence.":[157],"This":[158],"mechanism":[161],"gradually":[162],"incorporates":[163],"obtained":[165],"easy":[169],"patterns":[171],"later":[173],"prediction":[176],"hard":[178],"patterns,":[179],"makes":[181],"consistent":[184],"more":[186],"reliable.":[187],"To":[188],"verify":[189],"effectiveness":[191],"our":[193,219],"proposed":[194],"method,":[195],"addition":[197],"widely":[200],"used":[201],"PCNN-based":[202],"architecture,":[203],"also":[205],"perform":[206],"experiment":[208],"on":[209,226],"BiLSTM":[210],"comparison.":[214],"The":[215],"results":[216],"demonstrate":[217],"that":[218],"approach":[220],"outperform":[222],"state-of-the-art":[224],"systems":[225],"popular":[228],"evaluation":[229],"dataset.":[230]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}