{"id":"https://openalex.org/W1138655186","doi":"https://doi.org/10.18653/v1/k15-1015","title":"Incremental Recurrent Neural Network Dependency Parser with Search-based Discriminative Training","display_name":"Incremental Recurrent Neural Network Dependency Parser with Search-based Discriminative Training","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W1138655186","doi":"https://doi.org/10.18653/v1/k15-1015","mag":"1138655186"},"language":"en","primary_location":{"id":"doi:10.18653/v1/k15-1015","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k15-1015","pdf_url":"https://www.aclweb.org/anthology/K15-1015.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/K15-1015.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067220251","display_name":"Majid Yazdani","orcid":"https://orcid.org/0000-0002-8065-2855"},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]},{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]}],"countries":["CH","FR"],"is_corresponding":false,"raw_author_name":"Majid Yazdani","raw_affiliation_strings":["Computer Science Department University of Geneva","University of Geneva;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department University of Geneva","institution_ids":["https://openalex.org/I114457229","https://openalex.org/I4210156583"]},{"raw_affiliation_string":"University of Geneva;","institution_ids":["https://openalex.org/I114457229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084321238","display_name":"James Henderson","orcid":"https://orcid.org/0000-0003-3714-4799"},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"James Henderson","raw_affiliation_strings":["Xerox Research Center Europe","Xerox;#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xerox Research Center Europe","institution_ids":["https://openalex.org/I33976269"]},{"raw_affiliation_string":"Xerox;#TAB#","institution_ids":["https://openalex.org/I33976269"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"142","last_page":"152"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9944000244140625,"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":0.8722490072250366},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8118391036987305},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.68419349193573},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6748572587966919},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.6213477253913879},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6102182269096375},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5977720618247986},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5521560311317444},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5184433460235596},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.45807382464408875},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4046034812927246},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38295847177505493},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3352447748184204},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3156018555164337},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16157189011573792},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08587217330932617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8722490072250366},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8118391036987305},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.68419349193573},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6748572587966919},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.6213477253913879},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6102182269096375},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5977720618247986},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5521560311317444},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5184433460235596},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.45807382464408875},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4046034812927246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38295847177505493},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3352447748184204},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3156018555164337},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16157189011573792},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08587217330932617},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/k15-1015","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k15-1015","pdf_url":"https://www.aclweb.org/anthology/K15-1015.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},{"id":"pmh:oai:unige.ch:unige:74747","is_oa":true,"landing_page_url":"https://archive-ouverte.unige.ch/unige:74747","pdf_url":null,"source":{"id":"https://openalex.org/S4306402259","display_name":"Archive ouverte UNIGE (University of Geneva)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114457229","host_organization_name":"University of Geneva","host_organization_lineage":["https://openalex.org/I114457229"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th Conference on Computational Language Learning pp. 142-152","raw_type":"info:eu-repo/semantics/bookPart"}],"best_oa_location":{"id":"doi:10.18653/v1/k15-1015","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k15-1015","pdf_url":"https://www.aclweb.org/anthology/K15-1015.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1138655186.pdf","grobid_xml":"https://content.openalex.org/works/W1138655186.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W22861983","https://openalex.org/W98255950","https://openalex.org/W162171320","https://openalex.org/W179875071","https://openalex.org/W196214544","https://openalex.org/W1423339008","https://openalex.org/W1497611705","https://openalex.org/W1515383068","https://openalex.org/W2015238682","https://openalex.org/W2098050104","https://openalex.org/W2104917081","https://openalex.org/W2108014210","https://openalex.org/W2113900137","https://openalex.org/W2116983617","https://openalex.org/W2117130368","https://openalex.org/W2122922389","https://openalex.org/W2128791906","https://openalex.org/W2133280805","https://openalex.org/W2137132216","https://openalex.org/W2140679639","https://openalex.org/W2142222368","https://openalex.org/W2143431851","https://openalex.org/W2144784110","https://openalex.org/W2147880316","https://openalex.org/W2158899491","https://openalex.org/W2250861254","https://openalex.org/W2251682575","https://openalex.org/W2400801499","https://openalex.org/W2541794668","https://openalex.org/W2952230511","https://openalex.org/W2953182116","https://openalex.org/W4205376586","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2251084681","https://openalex.org/W2098784136","https://openalex.org/W4241489294","https://openalex.org/W287510790","https://openalex.org/W3117798239","https://openalex.org/W63925617","https://openalex.org/W2968543375","https://openalex.org/W4288558800","https://openalex.org/W2888625260","https://openalex.org/W2953770453"],"abstract_inverted_index":{"We":[0,85],"propose":[1],"a":[2,14,48,64,107],"discriminatively":[3],"trained":[4],"recurrent":[5],"neural":[6],"network":[7],"(RNN)":[8],"that":[9,32],"predicts":[10],"the":[11,34,126],"actions":[12],"for":[13,94],"fast":[15],"and":[16,38,71,79,106],"accurate":[17],"shift-reduce":[18],"dependency":[19,131],"parser.":[20],"The":[21,112],"RNN":[22],"uses":[23,39],"its":[24,121],"output-dependent":[25],"model":[26,52],"structure":[27],"to":[28,41,67,75],"compute":[29],"hidden":[30],"vectors":[31],"encode":[33],"preceding":[35],"partial":[36],"parse,":[37],"them":[40],"estimate":[42],"probabilities":[43],"of":[44,82,109],"parser":[45,83,114],"actions.":[46,84],"Unlike":[47],"similar":[49],"previous":[50],"generative":[51,122],"This":[53],"beam":[54],"search":[55],"prunes":[56],"after":[57],"each":[58,68],"shift":[59,69],"action,":[60],"so":[61],"we":[62],"add":[63],"correctness":[65],"probability":[66],"action":[70],"train":[72],"this":[73],"score":[74],"discriminate":[76],"between":[77],"correct":[78],"incorrect":[80],"sequences":[81],"also":[86],"speed":[87],"up":[88],"parsing":[89,132],"time":[90],"by":[91],"caching":[92],"computations":[93],"frequent":[95],"feature":[96,137],"combinations,":[97],"including":[98],"during":[99],"training,":[100],"giving":[101],"us":[102],"both":[103],"faster":[104,119],"training":[105],"form":[108],"backoff":[110],"smoothing.":[111],"resulting":[113],"is":[115],"over":[116],"35":[117],"times":[118],"than":[120],"counterpart":[123],"with":[124],"nearly":[125],"same":[127],"accuracy,":[128],"producing":[129],"state-of-art":[130],"results":[133],"while":[134],"requiring":[135],"minimal":[136],"engineering.":[138]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":9}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
