{"id":"https://openalex.org/W2116505555","doi":"https://doi.org/10.1017/s135132491100026x","title":"A unified alignment algorithm for bilingual data","display_name":"A unified alignment algorithm for bilingual data","publication_year":2011,"publication_date":"2011-09-13","ids":{"openalex":"https://openalex.org/W2116505555","doi":"https://doi.org/10.1017/s135132491100026x","mag":"2116505555"},"language":"en","primary_location":{"id":"doi:10.1017/s135132491100026x","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s135132491100026x","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5001253909","display_name":"Christoph Tillmann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"CHRISTOPH TILLMANN","raw_affiliation_strings":["IBM T.J. Watson Research Center, Yorktown Heights, New York, NY 10598, USA","IBM, T.J. Watson Research Center, Yorktown Heights, New York, NY 10598 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown Heights, New York, NY 10598, USA","institution_ids":[]},{"raw_affiliation_string":"IBM, T.J. Watson Research Center, Yorktown Heights, New York, NY 10598 USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005647823","display_name":"Sanjika Hewavitharana","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"SANJIKA HEWAVITHARANA","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA 15213, USA","Carnegie-Mellon University, Pittsburgh, PA 15213 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA 15213, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, PA 15213 USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001253909"],"corresponding_institution_ids":["https://openalex.org/I4210114115"],"apc_list":null,"apc_paid":null,"fwci":0.4385,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7419376,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"19","issue":"1","first_page":"33","last_page":"60"},"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":0.9997000098228455,"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":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.9222090840339661},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6540521383285522},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5895389318466187},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5239850878715515},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.47748586535453796},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4447951018810272},{"id":"https://openalex.org/keywords/beam-search","display_name":"Beam search","score":0.4402984082698822},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4246419668197632},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.41825202107429504},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41661444306373596},{"id":"https://openalex.org/keywords/search-algorithm","display_name":"Search algorithm","score":0.38206714391708374},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32658809423446655},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.17501917481422424}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9222090840339661},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6540521383285522},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5895389318466187},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5239850878715515},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.47748586535453796},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4447951018810272},{"id":"https://openalex.org/C19889080","wikidata":"https://www.wikidata.org/wiki/Q2835852","display_name":"Beam search","level":3,"score":0.4402984082698822},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4246419668197632},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.41825202107429504},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41661444306373596},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.38206714391708374},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32658809423446655},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.17501917481422424},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s135132491100026x","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s135132491100026x","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W23077562","https://openalex.org/W75158669","https://openalex.org/W92412080","https://openalex.org/W245306944","https://openalex.org/W1497763703","https://openalex.org/W1501633760","https://openalex.org/W1594833364","https://openalex.org/W1880089301","https://openalex.org/W2000026602","https://openalex.org/W2006969979","https://openalex.org/W2033180919","https://openalex.org/W2047295649","https://openalex.org/W2051472952","https://openalex.org/W2056970273","https://openalex.org/W2101105183","https://openalex.org/W2102695322","https://openalex.org/W2106528607","https://openalex.org/W2107695330","https://openalex.org/W2116042738","https://openalex.org/W2117652747","https://openalex.org/W2119168550","https://openalex.org/W2138553032","https://openalex.org/W2140903445","https://openalex.org/W2153653739","https://openalex.org/W2155368638","https://openalex.org/W2158310256","https://openalex.org/W2166098990","https://openalex.org/W2168929382","https://openalex.org/W2588710172","https://openalex.org/W2758884106","https://openalex.org/W4206914775","https://openalex.org/W6629835057","https://openalex.org/W6652311901","https://openalex.org/W6658984579","https://openalex.org/W6664710996"],"related_works":["https://openalex.org/W4386269615","https://openalex.org/W4390091683","https://openalex.org/W1994919150","https://openalex.org/W58921990","https://openalex.org/W2204575588","https://openalex.org/W2081821176","https://openalex.org/W3084994579","https://openalex.org/W3106196307","https://openalex.org/W4320350517","https://openalex.org/W2998661990"],"abstract_inverted_index":{"Abstract":[0],"The":[1,77],"paper":[2],"presents":[3],"a":[4,23,38,85,119,144,146],"novel":[5,39],"unified":[6,44,120],"algorithm":[7,45,80,125],"for":[8,28],"aligning":[9],"sentences":[10],"with":[11],"their":[12],"translations":[13],"in":[14,37,84,178],"bilingual":[15],"data.":[16,90,114],"With":[17,115],"the":[18,33,43,62,89,97,100,116,124,170],"help":[19,117],"of":[20,52,96,99,118,165],"ideas":[21],"from":[22],"stack-based":[24],"dynamic":[25],"programming":[26],"decoder":[27],"speech":[29],"recognition":[30],"(Ney":[31],"1984),":[32],"search":[34,79,171],"is":[35,81,105,126,172],"parametrized":[36],"way":[40],"such":[41],"that":[42,54],"can":[46,67],"be":[47,68],"used":[48],"on":[49,143,154,175],"various":[50],"types":[51],"data":[53],"have":[55],"been":[56],"previously":[57],"handled":[58],"by":[59],"separate":[60],"implementations:":[61],"extracted":[63,163],"text":[64,159],"chunk":[65,160],"pairs":[66,161],"either":[69],"sub-sentential":[70],"pairs,":[71],"one-to-one,":[72],"or":[73],"many-to-many":[74],"sentence-level":[75,108,138],"pairs.":[76],"one-stage":[78],"carried":[82,173],"out":[83,164,174],"single":[86],"run":[87],"over":[88],"Its":[91],"memory":[92],"requirements":[93],"are":[94,141,162],"independent":[95],"length":[98],"source":[101],"document,":[102],"and":[103,134,148],"it":[104,129],"applicable":[106],"to":[107],"parallel":[109],"as":[110,112],"well":[111],"comparable":[113],"beam-search":[121],"candidate":[122],"pruning,":[123],"very":[127],"efficient:":[128],"avoids":[130],"any":[131],"document-level":[132],"pre-filtering":[133],"uses":[135],"less":[136],"restrictive":[137],"filtering.":[139],"Results":[140],"presented":[142],"Russian\u2013English,":[145],"Spanish\u2013English,":[147],"an":[149],"Arabic\u2013English":[150],"extraction":[151],"task.":[152],"Based":[153],"simple":[155],"word-based":[156],"scoring":[157],"features,":[158],"several":[166],"trillion":[167],"candidates,":[168],"where":[169],"300":[176],"processors":[177],"parallel.":[179]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}