{"id":"https://openalex.org/W138910888","doi":null,"title":"Forest-based algorithms in natural language processing","display_name":"Forest-based algorithms in natural language processing","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W138910888","mag":"138910888"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.145.7644","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.7644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.upenn.edu/~lhuang3/Dissertation.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109994521","display_name":"Aravind K. Joshi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aravind K. Joshi","raw_affiliation_strings":["#N#               * University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106821597","display_name":"Kevin K. Knight","orcid":"https://orcid.org/0000-0001-9117-1718","observed_orcids":["https://orcid.org/0000-0001-9117-1718"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Knight","raw_affiliation_strings":["#N#               * University of Pennsylvania"],"raw_orcid":"https://orcid.org/0000-0001-9117-1718","affiliations":[{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006404928","display_name":"Liang Huang","orcid":"https://orcid.org/0000-0001-6444-7045","observed_orcids":["https://orcid.org/0000-0001-6444-7045"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Huang","raw_affiliation_strings":["#N#               * University of Pennsylvania"],"raw_orcid":"https://orcid.org/0000-0001-6444-7045","affiliations":[{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":1.3982,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.84907272,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T12031","display_name":"Speech and dialogue systems","score":0.0,"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/T10034","display_name":"Syntax, Semantics, Linguistic Variation","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/syntactic-analysis","display_name":"syntactic analysis","score":0.3529999852180481},{"id":"https://openalex.org/keywords/discriminative-training","display_name":"discriminative training","score":0.7039999961853027},{"id":"https://openalex.org/keywords/approximate-search","display_name":"approximate search","score":0.6470000147819519}],"concepts":[{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.917983889579773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8615694046020508},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7980701327323914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6445850133895874},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.5364824533462524},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.534646213054657},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5175178050994873},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5168667435646057},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.504593014717102},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.48611927032470703},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4543444812297821},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4404234290122986},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4393923580646515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33121731877326965},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0842980444431305},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.145.7644","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.7644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.upenn.edu/~lhuang3/Dissertation.pdf","raw_type":"text"},{"id":"pmh:oai:repository.upenn.edu:dissertations-8552","doi":null,"is_oa":false,"landing_page_url":"https://repository.upenn.edu/dissertations/AAI3346133","pdf_url":null,"source":{"id":"https://openalex.org/S4377196331","display_name":"Scholarly Commons (University of Pennsylvania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79576946","host_organization_name":"University of Pennsylvania","host_organization_lineage":["https://openalex.org/I79576946"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Dissertations available from ProQuest","raw_type":"text"},{"id":"mag:138910888","doi":null,"is_oa":false,"landing_page_url":"https://repository.upenn.edu/cgi/viewcontent.cgi?article=8552&context=dissertations","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":100,"referenced_works":["https://openalex.org/W76590478","https://openalex.org/W108437174","https://openalex.org/W125699335","https://openalex.org/W147273232","https://openalex.org/W179314280","https://openalex.org/W194033037","https://openalex.org/W1479669738","https://openalex.org/W1479758177","https://openalex.org/W1485071329","https://openalex.org/W1493576607","https://openalex.org/W1498238796","https://openalex.org/W1510052640","https://openalex.org/W1510137562","https://openalex.org/W1517284397","https://openalex.org/W1535015163","https://openalex.org/W1537309404","https://openalex.org/W1546862091","https://openalex.org/W1551104980","https://openalex.org/W1551202288","https://openalex.org/W1575907248","https://openalex.org/W1583697620","https://openalex.org/W1584587517","https://openalex.org/W1586368951","https://openalex.org/W1631260214","https://openalex.org/W1632114991","https://openalex.org/W1774330103","https://openalex.org/W1810157568","https://openalex.org/W1935980843","https://openalex.org/W1964388487","https://openalex.org/W1969483458","https://openalex.org/W1971799053","https://openalex.org/W1975638108","https://openalex.org/W1979495315","https://openalex.org/W1985754308","https://openalex.org/W1986372192","https://openalex.org/W1991133427","https://openalex.org/W1995809477","https://openalex.org/W2005712418","https://openalex.org/W2008652694","https://openalex.org/W2018116550","https://openalex.org/W2024060531","https://openalex.org/W2036830099","https://openalex.org/W2037894654","https://openalex.org/W2048808408","https://openalex.org/W2051818821","https://openalex.org/W2060535757","https://openalex.org/W2072016939","https://openalex.org/W2092654472","https://openalex.org/W2096765155","https://openalex.org/W2098050104","https://openalex.org/W2098823886","https://openalex.org/W2101105183","https://openalex.org/W2103738642","https://openalex.org/W2110104386","https://openalex.org/W2112777616","https://openalex.org/W2112900913","https://openalex.org/W2115289978","https://openalex.org/W2115753373","https://openalex.org/W2116316001","https://openalex.org/W2116410915","https://openalex.org/W2116957398","https://openalex.org/W2119168550","https://openalex.org/W2119314391","https://openalex.org/W2121127625","https://openalex.org/W2122472280","https://openalex.org/W2125528794","https://openalex.org/W2125712079","https://openalex.org/W2131297983","https://openalex.org/W2132382844","https://openalex.org/W2133590167","https://openalex.org/W2134275125","https://openalex.org/W2134729743","https://openalex.org/W2136657878","https://openalex.org/W2139621418","https://openalex.org/W2141732516","https://openalex.org/W2145227222","https://openalex.org/W2146418175","https://openalex.org/W2146574666","https://openalex.org/W2151170651","https://openalex.org/W2152096446","https://openalex.org/W2152263452","https://openalex.org/W2152302696","https://openalex.org/W2152907450","https://openalex.org/W2153653739","https://openalex.org/W2153800732","https://openalex.org/W2158388102","https://openalex.org/W2159506050","https://openalex.org/W2161227214","https://openalex.org/W2162245945","https://openalex.org/W2162539697","https://openalex.org/W2163568299","https://openalex.org/W2165666205","https://openalex.org/W2168194229","https://openalex.org/W2169362686","https://openalex.org/W2169755331","https://openalex.org/W2186159912","https://openalex.org/W2437005631","https://openalex.org/W2624992833","https://openalex.org/W2752885492","https://openalex.org/W2988806182"],"related_works":["https://openalex.org/W7099653081","https://openalex.org/W2137268927","https://openalex.org/W7096355898","https://openalex.org/W2085560712","https://openalex.org/W2110104386","https://openalex.org/W7099379489","https://openalex.org/W2037894654","https://openalex.org/W7098475943","https://openalex.org/W2146050252","https://openalex.org/W2161227214"],"abstract_inverted_index":{"Many":[0],"problems":[1],"in":[2,217,273,296,324],"Natural":[3],"Language":[4],"Processing":[5],"(NLP)":[6],"involves":[7],"an":[8,218],"efficient":[9,78],"search":[10,71,154,200],"for":[11,30,161,175,181],"the":[12,26,47,54,60,89,128,135,156,197,228,233,237,256,283,333,339],"best":[13,27,340],"derivation":[14],"over":[15],"(exponentially)":[16],"many":[17,279],"candidates.":[18],"For":[19],"example,":[20],"a":[21,31,38,41,66,244,252,260],"parser":[22],"aims":[23],"to":[24,137,152,203,236,305,343],"find":[25],"syntactic":[28],"tree":[29],"given":[32],"sentence":[33,258],"among":[34],"all":[35,50],"derivations":[36],"under":[37],"grammar,":[39],"and":[40,94,103,144,178,215,242,318,330],"machine":[42],"translation":[43,241,307,325],"(MT)":[44],"decoder":[45],"explores":[46],"space":[48],"of":[49,53,62,69,92,113,131,169,190,239,255,285,315,338],"possible":[51],"translations":[52],"source-language":[55],"sentence.":[56],"In":[57,183,196],"these":[58,150],"cases,":[59,185],"concept":[61],"packed":[63,253,310],"forest":[64,173,179,254],"provides":[65],"compact":[67],"representation":[68],"huge":[70],"spaces":[72],"by":[73],"sharing":[74],"common":[75],"sub-derivations,":[76],"where":[77,206],"algorithms":[79,107,133,151],"based":[80],"on":[81,108,120,227],"Dynamic":[82],"Programming":[83],"(DP)":[84],"are":[85,111,158],"possible.":[86],"Building":[87],"upon":[88],"hypergraph":[90],"formulation":[91],"forests":[93,157],"well-known":[95],"1-best":[96,267],"DP":[97,106],"algorithms,":[98],"this":[99,170,302],"dissertation":[100],"develops":[101],"fast":[102],"exact":[104,162],"k-best":[105],"forests,":[109],"which":[110],"orders":[112,189],"magnitudes":[114,191],"faster":[115,192,199],"than":[116,193,221,264],"previously":[117,223],"used":[118],"methods":[119,187],"state-of-the-art":[121],"parsers.":[122],"We":[123,147,164,299],"also":[124,201,300],"show":[125,321],"empirically":[126],"how":[127],"improved":[129],"output":[130],"our":[132,186,207],"has":[134],"potential":[136],"improve":[138],"results":[139,216,314],"from":[140,309],"parse":[141],"reranking":[142,180],"systems":[143,225,342],"other":[145],"applications.":[146],"then":[148],"extend":[149],"approximate":[153,208],"when":[155],"too":[159],"big":[160],"inference.":[163],"discuss":[165],"two":[166],"particular":[167],"instances":[168],"new":[171,245],"method,":[172],"rescoring":[174],"MT":[176],"decoding,":[177],"parsing.":[182],"both":[184],"perform":[188],"conventional":[194],"approaches.":[195],"latter,":[198],"leads":[202],"better":[204,220],"learning,":[205],"decoding":[209,317],"makes":[210],"whole-Treebank":[211],"discriminative":[212],"training":[213],"practical":[214],"accuracy":[219],"any":[222],"reported":[224],"trained":[226],"Treebank.":[229],"Finally,":[230],"we":[231],"apply":[232],"above":[234],"materials":[235],"problem":[238],"syntax-based":[240],"propose":[243],"paradigm,":[246],"forest-based":[247,316],"translation.":[248],"This":[249],"scheme":[250],"translates":[251],"source":[257],"into":[259,288],"target":[261],"sentence,":[262],"rather":[263],"just":[265],"using":[266],"or":[268],"k":[269],"-best":[270],"parses":[271],"as":[272],"usual":[274],"practice.":[275],"By":[276],"considering":[277],"exponentially":[278],"alternatives,":[280],"it":[281],"alleviates":[282],"propagation":[284],"parsing":[286],"errors":[287],"translation,":[289],"yet":[290],"only":[291],"comes":[292],"with":[293,327],"fractional":[294],"overhead":[295],"running":[297],"time.":[298],"push":[301],"direction":[303],"further":[304],"extract":[306],"rules":[308],"forests.":[311],"The":[312],"combined":[313],"rule":[319],"extraction":[320],"significant":[322],"improvements":[323],"quality":[326],"large-scale":[328],"experiments,":[329],"consistently":[331],"outperform":[332],"hierarchical":[334],"system":[335],"Hiero,":[336],"one":[337],"performing":[341],"date.":[344]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
