{"id":"https://openalex.org/W3203276480","doi":null,"title":"Unpacking and Transforming Feature Functions: New Ways to Smooth Phrase Tables","display_name":"Unpacking and Transforming Feature Functions: New Ways to Smooth Phrase Tables","publication_year":2011,"publication_date":"2011-09-19","ids":{"openalex":"https://openalex.org/W3203276480","mag":"3203276480"},"language":"en","primary_location":{"id":"pmh:oai:cisti-icist.nrc-cnrc.ca:cistinparc:21267976","doi":null,"is_oa":true,"landing_page_url":"https://nrc-publications.canada.ca/fra/voir/objet/?id=f943e893-18a5-4f0b-95db-6e080fedb4bb","pdf_url":"https://nrc-publications.canada.ca/eng/view/accepted/?id=f943e893-18a5-4f0b-95db-6e080fedb4bb","source":{"id":"https://openalex.org/S7407055245","display_name":"NPARC","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://nrc-publications.canada.ca/eng/view/accepted/?id=f943e893-18a5-4f0b-95db-6e080fedb4bb","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019715118","display_name":"Boxing Chen","orcid":"https://orcid.org/0000-0002-3170-4858","observed_orcids":["https://orcid.org/0000-0002-3170-4858"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boxing Chen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-3170-4858","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103230324","display_name":"Roland K\u00fchn","orcid":"https://orcid.org/0000-0002-1485-140X","observed_orcids":["https://orcid.org/0000-0002-1485-140X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roland K\u00fchn","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090694771","display_name":"George F. Foster","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"George Foster","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063990252","display_name":"Howard Johnson","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Howard Johnson","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6766,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.9410796,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"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":0.9976000189781189,"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":0.9976000189781189,"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":0.001500000013038516,"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":0.00019999999494757503,"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/phrase-based-machine-translation","display_name":"phrase-based statistical machine translation","score":0.878000020980835},{"id":"https://openalex.org/keywords/kneser-ney-smoothing","display_name":"Kneser-Ney smoothing","score":0.8960000276565552},{"id":"https://openalex.org/keywords/discounting","display_name":"discounting","score":0.5180000066757202}],"concepts":[{"id":"https://openalex.org/C2777256151","wikidata":"https://www.wikidata.org/wiki/Q7897273","display_name":"Unpacking","level":2,"score":0.9225910902023315},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6275362372398376},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.6062380075454712},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5161112546920776},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.41180139780044556},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3589848279953003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3555071949958801},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35522186756134033},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1690165400505066},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:cisti-icist.nrc-cnrc.ca:cistinparc:21267976","doi":null,"is_oa":true,"landing_page_url":"https://nrc-publications.canada.ca/fra/voir/objet/?id=f943e893-18a5-4f0b-95db-6e080fedb4bb","pdf_url":"https://nrc-publications.canada.ca/eng/view/accepted/?id=f943e893-18a5-4f0b-95db-6e080fedb4bb","source":{"id":"https://openalex.org/S7407055245","display_name":"NPARC","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.713.2702","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.713.2702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.iro.umontreal.ca/%7Efoster/papers/tuff-smoothing-mts11.pdf","raw_type":"text"},{"id":"mag:3203276480","doi":null,"is_oa":false,"landing_page_url":"https://aclanthology.org/2011.mtsummit-papers.30/","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":{"id":"pmh:oai:cisti-icist.nrc-cnrc.ca:cistinparc:21267976","doi":null,"is_oa":true,"landing_page_url":"https://nrc-publications.canada.ca/fra/voir/objet/?id=f943e893-18a5-4f0b-95db-6e080fedb4bb","pdf_url":"https://nrc-publications.canada.ca/eng/view/accepted/?id=f943e893-18a5-4f0b-95db-6e080fedb4bb","source":{"id":"https://openalex.org/S7407055245","display_name":"NPARC","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3203276480.pdf","grobid_xml":"https://content.openalex.org/works/W3203276480.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W24102868","https://openalex.org/W132913264","https://openalex.org/W193080678","https://openalex.org/W222053410","https://openalex.org/W2006969979","https://openalex.org/W2038698865","https://openalex.org/W2059800182","https://openalex.org/W2105891181","https://openalex.org/W2117827367","https://openalex.org/W2123635983","https://openalex.org/W2124807415","https://openalex.org/W2140343992","https://openalex.org/W2153653739","https://openalex.org/W2154124206","https://openalex.org/W2156985047","https://openalex.org/W2158195707","https://openalex.org/W2165357419","https://openalex.org/W2400634996"],"related_works":["https://openalex.org/W2117827367","https://openalex.org/W1909398668","https://openalex.org/W1574100934","https://openalex.org/W2997005750","https://openalex.org/W7099450175","https://openalex.org/W2136180489","https://openalex.org/W2183748887","https://openalex.org/W2578511464","https://openalex.org/W7100522835","https://openalex.org/W2155702883"],"abstract_inverted_index":{"State":[0],"of":[1,26,45,68,86,145],"the":[2,15,42,46,75,81,146,155],"art":[3],"phrase-based":[4],"statistical":[5],"machine":[6],"translation":[7,20],"systems":[8,88],"typically":[9],"contain":[10],"two":[11,32,69],"features":[12,36,66,77,97,115,118],"which":[13],"estimate":[14],"\u201cforward\u201d":[16],"and":[17,28,48,51,93,112,129],"\u201cbackward\u201d":[18],"conditional":[19],"probabilities":[21],"for":[22],"a":[23,124],"given":[24],"pair":[25],"source":[27,47],"target":[29,49],"phrase.":[30],"These":[31],"\u201crelative":[33],"frequency\u201d":[34],"(RF)":[35],"are":[37,101],"derived":[38,119],"from":[39,120],"three":[40,60,85],"counts:":[41],"joint":[43],"count":[44],"phrase":[50,157],"their":[52],"marginal":[53],"counts.":[54],"We":[55],"propose":[56],"to":[57,116,123,130,140],"\u201cunpack\u201d":[58],"these":[59,95],"statistics,":[61],"making":[62],"them":[63],"independent":[64],"\u201c3-count\u201d":[65],"instead":[67],"RF":[70,82],"features.":[71],"In":[72,152],"our":[73,153],"experiments,":[74,154],"3-count":[76,96,111,114,137],"perform":[78],"better":[79,142],"than":[80,143],"ones":[83],"in":[84],"four":[87],"we":[89,109],"tested.":[90],"By":[91],"transforming":[92],"generalizing":[94],"slightly,":[98],"further":[99],"improvements":[100],"obtained.":[102],"Furthermore,":[103],"under":[104],"several":[105,131],"different":[106],"experimental":[107],"conditions,":[108],"compare":[110],"generalized":[113],"new":[117,125],"Kneser-Ney":[121],"smoothing,":[122],"low-frequency":[126],"penalty":[127],"feature,":[128],"known":[132],"smoothing/":[133],"discounting":[134],"schemes.":[135],"Generalized":[136],"performs":[138],"similarly":[139],"or":[141],"all":[144],"smoothing":[147,162],"methods":[148],"except":[149],"modified":[150],"Kneser-Ney.":[151],"best":[156],"table":[158],"(not":[159],"language":[160],"model)":[161],"yields":[163],"+0.6-1.4":[164],"BLEU.":[165]},"counts_by_year":[{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2021-10-11T00:00:00"}