乐胖代购免代理版

{"id":"https://openalex.org/W1596148575","doi":"https://doi.org/10.1109/icassp.2000.862079","title":"A unified approach to statistical language modeling for Chinese","display_name":"A unified approach to statistical language modeling for Chinese","publication_year":2002,"publication_date":"2002-11-07","ids":{"openalex":"https://openalex.org/W1596148575","doi":"https://doi.org/10.1109/icassp.2000.862079","mag":"1596148575"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2000.862079","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5114910293","display_name":"Jianfeng Gao","orcid":"https://orcid.org/0000-0002-5702-6143"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"None Jianfeng Gao","raw_affiliation_strings":["Microsoft Research China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research China, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386394","display_name":"Haifeng Wang","orcid":"https://orcid.org/0000-0002-0672-7468"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"None Hai-Feng Wang","raw_affiliation_strings":["Microsoft Research China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research China, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061131131","display_name":"Mingjing Li","orcid":"https://orcid.org/0000-0002-5290-8104"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"None Mingjing Li","raw_affiliation_strings":["Microsoft Research China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research China, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065942185","display_name":"Kai-Fu Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"None Kai-Fu Lee","raw_affiliation_strings":["Microsoft Research China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research China, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.54,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.795483,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":88},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9997,"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":0.9997,"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":0.998,"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":0.9937,"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/pinyin","display_name":"Pinyin","score":0.8589182},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.53082937}],"concepts":[{"id":"https://openalex.org/C137546455","wikidata":"https://www.wikidata.org/wiki/Q3213474","display_name":"Trigram","level":2,"score":0.98113924},{"id":"https://openalex.org/C2781095461","wikidata":"https://www.wikidata.org/wiki/Q42222","display_name":"Pinyin","level":3,"score":0.8589182},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.8000889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7732117},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.67459524},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.65350664},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6255835},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.60068303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.58083135},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.53082937},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.52628547},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34169856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13800544},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.11065364},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2000.862079","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Quality education","id":"https://metadata.un.org/sdg/4"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":12,"referenced_works":["https://openalex.org/W1557757161","https://openalex.org/W1574901103","https://openalex.org/W1797288984","https://openalex.org/W1903115690","https://openalex.org/W1996034123","https://openalex.org/W2069598966","https://openalex.org/W2071184380","https://openalex.org/W2095368471","https://openalex.org/W2110145858","https://openalex.org/W2164547069","https://openalex.org/W2441154163","https://openalex.org/W265531733"],"related_works":["https://openalex.org/W4255764218","https://openalex.org/W2250909759","https://openalex.org/W2123672980","https://openalex.org/W2105076537","https://openalex.org/W2072223048","https://openalex.org/W2041167939","https://openalex.org/W2020757772","https://openalex.org/W2002221802","https://openalex.org/W1974967573","https://openalex.org/W1596148575"],"abstract_inverted_index":{"The":[0],"paper":[1],"presents":[2],"a":[3,44,56,65,78],"unified":[4,50],"approach":[5,51],"to":[6,17,97],"Chinese":[7,18],"statistical":[8],"language":[9],"modeling":[10],"(SLM).":[11],"Applying":[12],"SLM":[13],"techniques":[14],"like":[15],"trigrams":[16],"is":[19,24,43,83],"challenging":[20],"because:":[21],"(1)":[22],"there":[23,42],"no":[25],"standard":[26,100],"definition":[27],"of":[28,46,93],"words":[29],"in":[30],"Chinese,":[31],"(2)":[32],"word":[33],"boundaries":[34],"are":[35],"not":[36],"marked":[37],"by":[38],"spaces,":[39],"and":[40,53,68,102],"(3)":[41],"dearth":[45],"training":[47,58,71],"data.":[48],"Our":[49],"automatically":[52],"consistently":[54],"gathers":[55],"high-quality":[57,66],"data":[59,72],"set":[60],"from":[61],"the":[62,70,86,94,104,108],"Web,":[63],"creates":[64],"lexicon,":[67,75],"segments":[69],"using":[73,77],"this":[74],"all":[76],"maximum":[79],"likelihood":[80],"principle,":[81],"which":[82],"consistent":[84],"with":[85],"trigram":[87],"training.":[88],"We":[89],"show":[90],"that":[91,103],"each":[92],"methods":[95],"leads":[96],"improvements":[98],"over":[99],"SLM,":[101],"combined":[105],"method":[106],"yields":[107],"best":[109],"pinyin":[110],"conversion":[111],"result":[112],"reported.":[113]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1596148575","counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2024-12-12T21:35:41.353735","created_date":"2016-06-24"}