乐胖代购免代理版

{"id":"https://openalex.org/W2952768212","doi":"https://doi.org/10.18653/v1/p19-1024","title":"Attention Guided Graph Convolutional Networks for Relation Extraction","display_name":"Attention Guided Graph Convolutional Networks for Relation Extraction","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2952768212","doi":"https://doi.org/10.18653/v1/p19-1024","mag":"2952768212"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1024","pdf_url":"https://www.aclweb.org/anthology/P19-1024.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"preprint","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.aclweb.org/anthology/P19-1024.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061941569","display_name":"Zhijiang Guo","orcid":"https://orcid.org/0000-0002-6232-5957"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"funder","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhijiang Guo","raw_affiliation_strings":["StatNLP Research Group Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"StatNLP Research Group Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456377","display_name":"Yan Zhang","orcid":"https://orcid.org/0000-0003-1585-0801"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"funder","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yan Zhang","raw_affiliation_strings":["StatNLP Research Group Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"StatNLP Research Group Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045807606","display_name":"Wei Lu","orcid":"https://orcid.org/0000-0003-0827-0382"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"funder","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wei Lu","raw_affiliation_strings":["StatNLP Research Group Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"StatNLP Research Group Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":447,"citation_normalized_percentile":{"value":0.999928,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9996,"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":0.9982,"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/relationship-extraction","display_name":"Relationship extraction","score":0.83409685},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.75954217},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.53762746},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5092331},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4223271}],"concepts":[{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.83409685},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8087377},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.75954217},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.7116198},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5809683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.55859697},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.550957},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.53762746},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.53722537},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5092331},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4926787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43948588},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4223271},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39806113},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38068968},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3715975},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1024","pdf_url":"https://www.aclweb.org/anthology/P19-1024.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.07510","pdf_url":"http://arxiv.org/pdf/1906.07510","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1024","pdf_url":"https://www.aclweb.org/anthology/P19-1024.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":48,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1514535095","https://openalex.org/W1551842868","https://openalex.org/W1887754209","https://openalex.org/W2107598941","https://openalex.org/W2133564696","https://openalex.org/W2136566870","https://openalex.org/W2138627627","https://openalex.org/W2149997683","https://openalex.org/W2162590473","https://openalex.org/W2181042685","https://openalex.org/W2250521169","https://openalex.org/W2250539671","https://openalex.org/W2251622960","https://openalex.org/W2267186426","https://openalex.org/W2513378248","https://openalex.org/W2517194566","https://openalex.org/W2600702321","https://openalex.org/W2612364175","https://openalex.org/W2759211898","https://openalex.org/W2804057010","https://openalex.org/W2889224519","https://openalex.org/W2892094955","https://openalex.org/W2899771611","https://openalex.org/W2951309718","https://openalex.org/W2962785888","https://openalex.org/W2963020213","https://openalex.org/W2963021258","https://openalex.org/W2963171262","https://openalex.org/W2963355447","https://openalex.org/W2963403868","https://openalex.org/W2963446712","https://openalex.org/W2963653811","https://openalex.org/W2963655104","https://openalex.org/W2963858333","https://openalex.org/W2963907629","https://openalex.org/W2964015378","https://openalex.org/W2964114465","https://openalex.org/W2964167098","https://openalex.org/W2964193968","https://openalex.org/W2964217331","https://openalex.org/W2964222246","https://openalex.org/W2964308564","https://openalex.org/W2964311892","https://openalex.org/W2964321699","https://openalex.org/W4297733535","https://openalex.org/W4385245566","https://openalex.org/W637153065"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W3138801416","https://openalex.org/W2594363579","https://openalex.org/W2444550338","https://openalex.org/W2369351710","https://openalex.org/W2352298027","https://openalex.org/W2315233710","https://openalex.org/W2169232658","https://openalex.org/W2092919065"],"abstract_inverted_index":{"Dependency":[0],"trees":[1,33,77],"convey":[2],"rich":[3],"structural":[4,131],"information":[5,25,29,132],"that":[6,89,122],"is":[7,125],"proven":[8],"useful":[9,100],"for":[10,46,101],"extracting":[11],"relations":[12],"among":[13],"entities":[14],"in":[15],"text.":[16],"However,":[17],"how":[18,92],"to":[19,93,96,127],"effectively":[20],"make":[21],"use":[22],"of":[23,133],"relevant":[24,48,98],"while":[26],"ignoring":[27],"irrelevant":[28],"from":[30],"the":[31,97,102,130,134],"dependency":[32,50,76,136],"remains":[34],"a":[35,69,86],"challenging":[36],"research":[37],"question.":[38],"Existing":[39],"approaches":[40],"employing":[41],"rule":[42],"based":[43],"hard-pruning":[44],"strategies":[45],"selecting":[47],"partial":[49],"structures":[51],"may":[52],"not":[53],"always":[54],"yield":[55],"optimal":[56],"results.":[57],"In":[58],"this":[59],"work,":[60],"we":[61],"propose":[62],"Attention":[63],"Guided":[64],"Graph":[65],"Convolutional":[66],"Networks":[67],"(AGGCNs),":[68],"novel":[70],"model":[71,81,124],"which":[72],"directly":[73],"takes":[74],"full":[75,135],"as":[78,85],"inputs.":[79],"Our":[80],"can":[82],"be":[83],"understood":[84],"soft-pruning":[87],"approach":[88],"automatically":[90],"learns":[91],"selectively":[94],"attend":[95],"sub-structures":[99],"relation":[103,114,119],"extraction":[104,115,120],"task.":[105],"Extensive":[106],"results":[107,141],"on":[108],"various":[109],"tasks":[110],"including":[111],"cross-sentence":[112],"n-ary":[113],"and":[116],"large-scale":[117],"sentence-level":[118],"show":[121],"our":[123],"able":[126],"better":[128,140],"leverage":[129],"trees,":[137],"giving":[138],"significantly":[139],"than":[142],"previous":[143],"approaches.":[144]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2952768212","counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":40},{"year":2023,"cited_by_count":93},{"year":2022,"cited_by_count":81},{"year":2021,"cited_by_count":148},{"year":2020,"cited_by_count":70},{"year":2019,"cited_by_count":10}],"updated_date":"2025-04-07T03:24:20.146112","created_date":"2019-06-27"}