{"id":"https://openalex.org/W2545354433","doi":"https://doi.org/10.1109/nlpke.2011.6138170","title":"A comparison study of candidate generation for Chinese word segmentation","display_name":"A comparison study of candidate generation for Chinese word segmentation","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2545354433","doi":"https://doi.org/10.1109/nlpke.2011.6138170","mag":"2545354433"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2011.6138170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2011.6138170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 7th International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-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/A5034444288","display_name":"Kaixu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kaixu Zhang","raw_affiliation_strings":["State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046448314","display_name":"Maosong Sun","orcid":"https://orcid.org/0000-0002-6011-6115"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maosong Sun","raw_affiliation_strings":["State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034444288"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.8552,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82008718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"45","issue":null,"first_page":"60","last_page":"67"},"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":0.9998000264167786,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7668332457542419},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7572446465492249},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.6690002083778381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5811412930488586},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5575650930404663},{"id":"https://openalex.org/keywords/star-schema","display_name":"Star schema","score":0.4738902449607849},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39208948612213135},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38983434438705444},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3252737522125244},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.26870280504226685},{"id":"https://openalex.org/keywords/database-schema","display_name":"Database schema","score":0.2560705840587616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1600547730922699}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7668332457542419},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7572446465492249},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.6690002083778381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5811412930488586},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5575650930404663},{"id":"https://openalex.org/C190703929","wikidata":"https://www.wikidata.org/wiki/Q1331138","display_name":"Star schema","level":4,"score":0.4738902449607849},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39208948612213135},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38983434438705444},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3252737522125244},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26870280504226685},{"id":"https://openalex.org/C30775581","wikidata":"https://www.wikidata.org/wiki/Q632285","display_name":"Database schema","level":3,"score":0.2560705840587616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1600547730922699},{"id":"https://openalex.org/C148840519","wikidata":"https://www.wikidata.org/wiki/Q1049878","display_name":"Database design","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nlpke.2011.6138170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2011.6138170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 7th International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W25062297","https://openalex.org/W86604388","https://openalex.org/W1574901103","https://openalex.org/W1575907248","https://openalex.org/W1648907545","https://openalex.org/W1979145089","https://openalex.org/W1979711143","https://openalex.org/W2008652694","https://openalex.org/W2035304092","https://openalex.org/W2036516910","https://openalex.org/W2063925051","https://openalex.org/W2102461220","https://openalex.org/W2110974939","https://openalex.org/W2131988669","https://openalex.org/W2132961219","https://openalex.org/W2159406587","https://openalex.org/W2160097208","https://openalex.org/W2163377725","https://openalex.org/W2165209288","https://openalex.org/W2165664509","https://openalex.org/W3145501851","https://openalex.org/W4249572517","https://openalex.org/W6600965556","https://openalex.org/W6603570391","https://openalex.org/W6634451464","https://openalex.org/W6637028267","https://openalex.org/W6659530292","https://openalex.org/W6676509622","https://openalex.org/W6679405094","https://openalex.org/W6683437210","https://openalex.org/W6683599074","https://openalex.org/W6683955732","https://openalex.org/W6684279925","https://openalex.org/W6684544359"],"related_works":["https://openalex.org/W2034415381","https://openalex.org/W1678653077","https://openalex.org/W160336554","https://openalex.org/W2389917040","https://openalex.org/W2391783634","https://openalex.org/W2167394053","https://openalex.org/W4245142254","https://openalex.org/W3038511590","https://openalex.org/W2135596909","https://openalex.org/W273624747"],"abstract_inverted_index":{"Chinese":[0],"word":[1,76,116],"segmentation":[2,144,159],"can":[3],"be":[4],"implemented":[5],"in":[6,54,83,104,140,155],"a":[7,13,20,33,38,84,105],"coarse-to-fine":[8,134,171],"schema.":[9,191],"In":[10],"such":[11],"schema,":[12],"candidate":[14,56,69,92,126],"set":[15,57],"containing":[16],"multiple":[17],"segmentations":[18,53],"of":[19,32,46,90,94,169,178,188],"sentence":[21,80],"(rather":[22],"than":[23,185],"only":[24,142],"one":[25,143],"segmentation)":[26],"is":[27,145,160,173],"used":[28,146,161],"as":[29],"the":[30,52,55,60,91,115,120,133,137,148,152,163,167,170,176,179,186,189],"output":[31],"coarse-grained":[34],"CWS":[35,41,107],"model.":[36],"Then":[37],"more":[39],"sophisticated":[40],"model":[42],"or":[43],"other":[44],"models":[45],"downstream":[47,149,164],"tasks":[48],"will":[49],"reconsider":[50],"all":[51,157],"to":[58,175],"determine":[59],"best":[61,121],"segmentation.":[62],"This":[63],"paper":[64],"discussed":[65],"and":[66,79,108,151,182],"compared":[67,103],"three":[68,125],"generation":[70,127],"methods,":[71],"namely":[72],"boundary":[73],"level":[74,77,81,117],"method,":[75,82],"method":[78,118],"unified":[85],"form.":[86],"The":[87,99,111],"oracle":[88],"F1-measures":[89],"sets":[93],"these":[95,124],"methods":[96],"were":[97,101],"compared.":[98],"performances":[100],"also":[102,130],"joint":[106,153,190],"POS-tagging":[109],"task.":[110,165],"results":[112],"showed":[113,131],"that":[114,132],"has":[119],"performance":[122],"among":[123],"methods.":[128],"Results":[129],"schema":[135,139,154,172,181],"outperforms":[136],"pipeline":[138,180],"which":[141,156],"for":[147,162],"task":[150],"possible":[158],"Moreover,":[166],"speed":[168,177,187],"closed":[174],"much":[183],"higher":[184]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
