{"id":"https://openalex.org/W2104917081","doi":"https://doi.org/10.3115/1218955.1218970","title":"Incremental parsing with the perceptron algorithm","display_name":"Incremental parsing with the perceptron algorithm","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2104917081","doi":"https://doi.org/10.3115/1218955.1218970","mag":"2104917081"},"language":"en","primary_location":{"id":"doi:10.3115/1218955.1218970","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1218955.1218970","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1218955.1218970","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics  - ACL '04","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.3115/1218955.1218970","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079061237","display_name":"Michael Collins","orcid":"https://orcid.org/0000-0003-0997-1527"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Michael Collins","raw_affiliation_strings":["MIT CSAIL"],"affiliations":[{"raw_affiliation_string":"MIT CSAIL","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020068498","display_name":"Brian Roark","orcid":null},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Roark","raw_affiliation_strings":["AT&T Labs -- Research","AT&T Labs--Research"],"affiliations":[{"raw_affiliation_string":"AT&T Labs -- Research","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Labs--Research","institution_ids":["https://openalex.org/I1283103587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079061237"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":20.8156,"has_fulltext":true,"cited_by_count":385,"citation_normalized_percentile":{"value":0.99382337,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"es"},"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":0.996999979019165,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9861999750137329,"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/treebank","display_name":"Treebank","score":0.962854266166687},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.8025393486022949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7452676296234131},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.7428054213523865},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6619676947593689},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6396870613098145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6136813759803772},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5712488293647766},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5400638580322266},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4716039299964905},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.46823447942733765},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43445661664009094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4244518280029297},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4079150855541229},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3121281564235687},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.0764533281326294}],"concepts":[{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.962854266166687},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8025393486022949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7452676296234131},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.7428054213523865},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6619676947593689},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6396870613098145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6136813759803772},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5712488293647766},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5400638580322266},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4716039299964905},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.46823447942733765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43445661664009094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4244518280029297},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4079150855541229},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3121281564235687},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0764533281326294},{"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:10.3115/1218955.1218970","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1218955.1218970","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1218955.1218970","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics  - ACL '04","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.104.5264","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.5264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://acl.ldc.upenn.edu/acl2004/main/pdf/338_pdf_2-col.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/1218955.1218970","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1218955.1218970","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1218955.1218970","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics  - ACL '04","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4858157342","display_name":null,"funder_award_id":"347631","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8139857883","display_name":"CAREER: Statistical Learning Theory for Natural Language Processing: Theory, Algorithms and Representations","funder_award_id":"0347631","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309370","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2104917081.pdf","grobid_xml":"https://content.openalex.org/works/W2104917081.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W8949146","https://openalex.org/W1491745322","https://openalex.org/W1530801890","https://openalex.org/W1551104980","https://openalex.org/W1552767446","https://openalex.org/W1642730643","https://openalex.org/W1734853756","https://openalex.org/W1953828586","https://openalex.org/W1979711143","https://openalex.org/W2008652694","https://openalex.org/W2020145626","https://openalex.org/W2098379588","https://openalex.org/W2104118994","https://openalex.org/W2109902858","https://openalex.org/W2111417482","https://openalex.org/W2121127625","https://openalex.org/W2123893795","https://openalex.org/W2124445791","https://openalex.org/W2131297983","https://openalex.org/W2143458716","https://openalex.org/W2147880316","https://openalex.org/W2160842254","https://openalex.org/W3021452258","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W1043255351","https://openalex.org/W2135057643","https://openalex.org/W2109902858","https://openalex.org/W1533278948","https://openalex.org/W1781980207","https://openalex.org/W2951759144","https://openalex.org/W28706907","https://openalex.org/W2949524199","https://openalex.org/W2575884139","https://openalex.org/W2017946383"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"an":[3,45],"incremental":[4],"parsing":[5,65],"approach":[6,34],"where":[7],"parameters":[8],"are":[9],"estimated":[10],"using":[11],"a":[12,73,85],"variant":[13],"of":[14,29,44],"the":[15,30,38,61,66,79,91],"perceptron":[16,33,74],"algorithm.":[17],"A":[18],"beam-search":[19],"algorithm":[20],"is":[21],"used":[22],"during":[23,82],"both":[24],"training":[25,72],"and":[26,51],"decoding":[27],"phases":[28],"method.":[31],"The":[32],"was":[35],"implemented":[36],"with":[37,78],"same":[39],"feature":[40],"set":[41],"as":[42],"that":[43,55,71],"existing":[46],"generative":[47,62,80,92],"model":[48,63,75,81,93],"(Roark,":[49],"2001a),":[50],"experimental":[52],"results":[53],"show":[54],"it":[56],"gives":[57],"competitive":[58],"performance":[59],"to":[60,76,95],"on":[64],"Penn":[67],"treebank.":[68],"We":[69],"demonstrate":[70],"combine":[77],"search":[83],"provides":[84],"2.1":[86],"percent":[87],"F-measure":[88],"improvement":[89],"over":[90],"alone,":[94],"88.8":[96],"percent.":[97]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":30},{"year":2016,"cited_by_count":43},{"year":2015,"cited_by_count":44},{"year":2014,"cited_by_count":32},{"year":2013,"cited_by_count":28},{"year":2012,"cited_by_count":23}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
