{"id":"https://openalex.org/W2110683310","doi":"https://doi.org/10.3115/1075096.1075138","title":"Uncertainty reduction in collaborative bootstrapping","display_name":"Uncertainty reduction in collaborative bootstrapping","publication_year":2003,"publication_date":"2003-01-01","ids":{"openalex":"https://openalex.org/W2110683310","doi":"https://doi.org/10.3115/1075096.1075138","mag":"2110683310"},"language":"en","primary_location":{"id":"doi:10.3115/1075096.1075138","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1075096.1075138","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=1075138&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st Annual Meeting on Association for Computational Linguistics  - ACL '03","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=1075138&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011542448","display_name":"Yunbo Cao","orcid":"https://orcid.org/0009-0005-2558-5206"},"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"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Yunbo Cao","raw_affiliation_strings":["Microsoft Research Asia, Haidian, Beijing, China","[Microsoft Research Asia, Haidian, Beijing, China]"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"[Microsoft Research Asia, Haidian, Beijing, China]","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455129","display_name":"Hang Li","orcid":"https://orcid.org/0000-0002-1230-4007"},"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"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Hang Li","raw_affiliation_strings":["Microsoft Research Asia, Haidian, Beijing, China","[Microsoft Research Asia, Haidian, Beijing, China]"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"[Microsoft Research Asia, Haidian, Beijing, China]","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100317802","display_name":"Lian Li","orcid":"https://orcid.org/0000-0002-4476-0541"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Lian","raw_affiliation_strings":["Fudan University, Shanghai, China","Fudan University Shanghai, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Fudan University Shanghai, China#TAB#","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011542448"],"corresponding_institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"],"apc_list":null,"apc_paid":null,"fwci":2.2847,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.89649648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"327","last_page":"334"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9983000159263611,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9930999875068665,"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/bootstrapping","display_name":"Bootstrapping (finance)","score":0.9656316041946411},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7315446734428406},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.7310420870780945},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6109980344772339},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5662263035774231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45260491967201233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40134018659591675},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3849225640296936},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.29408547282218933},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.19940009713172913},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19495251774787903}],"concepts":[{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.9656316041946411},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7315446734428406},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7310420870780945},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6109980344772339},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5662263035774231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45260491967201233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40134018659591675},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3849225640296936},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29408547282218933},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.19940009713172913},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19495251774787903},{"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":[{"id":"doi:10.3115/1075096.1075138","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1075096.1075138","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=1075138&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st Annual Meeting on Association for Computational Linguistics  - ACL '03","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.3115/1075096.1075138","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1075096.1075138","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=1075138&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st Annual Meeting on Association for Computational Linguistics  - ACL '03","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6499999761581421,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2110683310.pdf","grobid_xml":"https://content.openalex.org/works/W2110683310.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1579429723","https://openalex.org/W1593345689","https://openalex.org/W2037603696","https://openalex.org/W2048679005","https://openalex.org/W2085989833","https://openalex.org/W2096152098","https://openalex.org/W2101210369","https://openalex.org/W2107540895","https://openalex.org/W2118669325","https://openalex.org/W2140076625","https://openalex.org/W2785349534","https://openalex.org/W2883783597","https://openalex.org/W6753223686"],"related_works":["https://openalex.org/W1667647204","https://openalex.org/W2404647514","https://openalex.org/W4247536566","https://openalex.org/W1534274833","https://openalex.org/W4241418540","https://openalex.org/W2018477250","https://openalex.org/W3119814709","https://openalex.org/W1508895727","https://openalex.org/W2725786787","https://openalex.org/W3117246195"],"abstract_inverted_index":{"This":[0],"paper":[1,30],"proposes":[2,47,76],"the":[3,41,53,59,67,84,93,96,101,104],"use":[4],"of":[5,43,55,58,71,80,86,95,103],"uncertainty":[6,33,56,87],"reduction":[7,34],"in":[8,22,62,69],"machine":[9],"learning":[10],"methods":[11],"such":[12],"as":[13,26],"co-training":[14],"and":[15,65,98],"bilingual":[16],"boot-strapping,":[17],"which":[18],"are":[19],"referred":[20],"to,":[21],"a":[23,48,77],"general":[24],"term,":[25],"'collaborative":[27],"bootstrapping'.":[28],"The":[29],"indicates":[31],"that":[32],"is":[35],"an":[36],"important":[37],"factor":[38],"for":[39,51],"enhancing":[40],"performance":[42],"collaborative":[44,63,72,81],"bootstrapping.":[45,73],"It":[46],"new":[49,78,105],"measure":[50,68],"representing":[52],"degree":[54],"correlation":[57],"two":[60],"classifiers":[61],"bootstrapping":[64,82],"uses":[66],"analysis":[70,97],"Furthermore,":[74],"it":[75],"algorithm":[79],"on":[83],"basis":[85],"reduction.":[88],"Experimental":[89],"results":[90],"have":[91,99],"verified":[92],"correctness":[94],"demonstrated":[100],"significance":[102],"algorithm.":[106]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}