{"id":"https://openalex.org/W3198489485","doi":"https://doi.org/10.1587/transinf.2020edp7249","title":"Gated Convolutional Neural Networks with Sentence-Related Selection for Distantly Supervised Relation Extraction","display_name":"Gated Convolutional Neural Networks with Sentence-Related Selection for Distantly Supervised Relation Extraction","publication_year":2021,"publication_date":"2021-08-31","ids":{"openalex":"https://openalex.org/W3198489485","doi":"https://doi.org/10.1587/transinf.2020edp7249","mag":"3198489485"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2020edp7249","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2020edp7249","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E104.D/9/E104.D_2020EDP7249/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E104.D/9/E104.D_2020EDP7249/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100394297","display_name":"Yufeng Chen","orcid":"https://orcid.org/0000-0003-0437-6788"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufeng CHEN","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100336560","display_name":"Siqi Li","orcid":"https://orcid.org/0000-0003-2085-4938"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi LI","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102845102","display_name":"Xingya Li","orcid":"https://orcid.org/0000-0002-8265-7318"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xingya LI","raw_affiliation_strings":["China Institute of Marine Technology & Economy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Institute of Marine Technology & Economy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101698034","display_name":"Jinan Xu","orcid":"https://orcid.org/0000-0003-0170-626X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinan XU","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101745046","display_name":"Jian Liu","orcid":"https://orcid.org/0000-0002-4728-5678"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian LIU","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, the School of Computer and Information Technology, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12995274,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"E104.D","issue":"9","first_page":"1486","last_page":"1495"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9610000252723694,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9610000252723694,"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":0.9491000175476074,"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":0.8687349557876587},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.8459292650222778},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6398279070854187},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6295695304870605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5937896370887756},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4733681380748749},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.46471723914146423},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.45689037442207336},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45526057481765747},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.44167229533195496},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.42322778701782227},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32679006457328796},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.1821037232875824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8687349557876587},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.8459292650222778},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6398279070854187},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6295695304870605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5937896370887756},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4733681380748749},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46471723914146423},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.45689037442207336},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45526057481765747},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.44167229533195496},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.42322778701782227},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32679006457328796},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.1821037232875824},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2020edp7249","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2020edp7249","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E104.D/9/E104.D_2020EDP7249/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2020edp7249","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2020edp7249","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E104.D/9/E104.D_2020EDP7249/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G106398601","display_name":null,"funder_award_id":"61976015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2153459869","display_name":null,"funder_award_id":"61876198","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7838506768","display_name":null,"funder_award_id":"61976016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8869255493","display_name":null,"funder_award_id":"61976016, 61976015, and 61876198","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":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3198489485.pdf","grobid_xml":"https://content.openalex.org/works/W3198489485.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W174427690","https://openalex.org/W1604644367","https://openalex.org/W1614298861","https://openalex.org/W2064675550","https://openalex.org/W2107598941","https://openalex.org/W2127795553","https://openalex.org/W2132679783","https://openalex.org/W2251135946","https://openalex.org/W2515462165","https://openalex.org/W2540404261","https://openalex.org/W2604610161","https://openalex.org/W2613904329","https://openalex.org/W2759996146","https://openalex.org/W2760600531","https://openalex.org/W2776652360","https://openalex.org/W2890021306","https://openalex.org/W2891417293","https://openalex.org/W2962939608","https://openalex.org/W2963443341","https://openalex.org/W2964173876","https://openalex.org/W2964317478","https://openalex.org/W2981111490","https://openalex.org/W2998209348","https://openalex.org/W3035996038","https://openalex.org/W3091791101"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4387688064","https://openalex.org/W2085384747","https://openalex.org/W2106071040","https://openalex.org/W2375873920","https://openalex.org/W2088166309","https://openalex.org/W4312133475","https://openalex.org/W4238976562","https://openalex.org/W2805262146","https://openalex.org/W4379517534"],"abstract_inverted_index":{"Relation":[0],"extraction":[1],"is":[2,17,100,118,130,143],"one":[3],"of":[4,38,176],"the":[5,30,39,50,171],"key":[6],"basic":[7],"tasks":[8],"in":[9,13,43,174],"natural":[10],"language":[11],"processing":[12],"which":[14,65,99],"distant":[15,44,97],"supervision":[16],"widely":[18],"used":[19],"for":[20,70],"obtaining":[21],"large-scale":[22],"labeled":[23],"data":[24,33],"without":[25],"expensive":[26],"labor":[27],"cost.":[28],"However,":[29],"automatically":[31],"generated":[32],"contains":[34],"massive":[35],"noise":[36,59,95,123,148,165],"because":[37],"wrong":[40],"labeling":[41],"problem":[42],"supervision.":[45],"To":[46],"address":[47],"this":[48,75],"problem,":[49],"existing":[51],"research":[52],"work":[53],"mainly":[54],"focuses":[55],"on":[56,154],"removing":[57],"sentence-level":[58,94,147,164],"with":[60,91,115],"various":[61],"sentence":[62],"selection":[63,141],"strategies,":[64],"however":[66],"could":[67],"be":[68],"incompetent":[69],"disposing":[71],"word-level":[72,92,122,162],"noise.":[73],"In":[74],"paper,":[76],"we":[77],"propose":[78],"a":[79,112,127,139],"novel":[80],"neural":[81],"framework":[82],"considering":[83],"both":[84,177],"intra-sentence":[85],"and":[86,93,137,163,179],"inter-sentence":[87],"relevance":[88],"to":[89,120,132,145],"deal":[90],"from":[96],"supervision,":[98],"denoted":[101],"as":[102],"Sentence-Related":[103],"Gated":[104],"Piecewise":[105],"Convolutional":[106],"Neural":[107],"Networks":[108],"(SR-GPCNN).":[109],"Specifically,":[110],"1)":[111],"gate":[113],"mechanism":[114],"multi-head":[116],"self-attention":[117],"adopted":[119],"reduce":[121],"inside":[124],"sentences;":[125],"2)":[126],"soft-label":[128],"strategy":[129],"utilized":[131],"alleviate":[133],"wrong-labeling":[134],"propagation":[135],"problem;":[136],"3)":[138],"sentence-related":[140],"model":[142],"designed":[144],"filter":[146],"further.":[149],"The":[150],"extensive":[151],"experimental":[152],"results":[153],"NYT":[155],"dataset":[156],"demonstrate":[157],"that":[158],"our":[159],"approach":[160],"filters":[161],"effectively,":[166],"thus":[167],"significantly":[168],"outperforms":[169],"all":[170],"baseline":[172],"models":[173],"terms":[175],"AUC":[178],"top-n":[180],"precision":[181],"metrics.":[182]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
