乐胖代购免代理版

{"id":"https://openalex.org/W2486791387","doi":"https://doi.org/10.1177/0142331216658091","title":"Improving semi-supervised self-training with embedded manifold transduction","display_name":"Improving semi-supervised self-training with embedded manifold transduction","publication_year":2016,"publication_date":"2016-07-27","ids":{"openalex":"https://openalex.org/W2486791387","doi":"https://doi.org/10.1177/0142331216658091","mag":"2486791387"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1177/0142331216658091","pdf_url":null,"source":{"id":"https://openalex.org/S24148485","display_name":"Transactions of the Institute of Measurement and Control","issn_l":"0142-3312","issn":["0142-3312","1477-0369"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5079607464","display_name":"Ye Tao","orcid":"https://orcid.org/0000-0002-3954-828X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"funder","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ye Tao","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027158285","display_name":"Duzhou Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"funder","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Duzhou Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068650017","display_name":"Shengjun Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"funder","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengjun Cheng","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100873220","display_name":"Xianglong Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"funder","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianglong Tang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5079607464"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.722,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":9,"citation_normalized_percentile":{"value":0.834462,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":85,"max":86},"biblio":{"volume":"40","issue":"2","first_page":"363","last_page":"374"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9972,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9972,"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":0.9962,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9925,"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/co-training","display_name":"Co-training","score":0.6469875},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.57737666},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5217077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.72097856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6572246},{"id":"https://openalex.org/C2776959682","wikidata":"https://www.wikidata.org/wiki/Q17005296","display_name":"Co-training","level":3,"score":0.6469875},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.63209033},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6317971},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.61840534},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.57737666},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.54924893},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5217077},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43834797},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40956116},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1177/0142331216658091","pdf_url":null,"source":{"id":"https://openalex.org/S24148485","display_name":"Transactions of the Institute of Measurement and Control","issn_l":"0142-3312","issn":["0142-3312","1477-0369"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61171184 and 61201309"}],"datasets":[],"versions":[],"referenced_works_count":21,"referenced_works":["https://openalex.org/W1493009343","https://openalex.org/W1594031697","https://openalex.org/W1969959732","https://openalex.org/W2011795890","https://openalex.org/W2056021151","https://openalex.org/W2057052429","https://openalex.org/W2078380024","https://openalex.org/W2079261742","https://openalex.org/W2098370488","https://openalex.org/W2099534828","https://openalex.org/W2111574971","https://openalex.org/W2123442489","https://openalex.org/W2133556223","https://openalex.org/W2134767644","https://openalex.org/W2137034166","https://openalex.org/W2153635508","https://openalex.org/W2159937720","https://openalex.org/W2165396616","https://openalex.org/W2167665791","https://openalex.org/W4244259635","https://openalex.org/W4252959399"],"related_works":["https://openalex.org/W4303683898","https://openalex.org/W2949671220","https://openalex.org/W2797776314","https://openalex.org/W2378187833","https://openalex.org/W2133556223","https://openalex.org/W2130553454","https://openalex.org/W2098708659","https://openalex.org/W2041453872","https://openalex.org/W1505796919","https://openalex.org/W121244246"],"abstract_inverted_index":{"Semi-supervised":[0],"learning":[1,12,27,37],"aims":[2],"to":[3,10,20,60,120,138,154,161,177,189],"utilize":[4],"both":[5],"labelled":[6,71,88,131,163],"and":[7,132,140],"unlabelled":[8,22,47,53,133,142,182],"data":[9,23,89,134],"improve":[11,204],"performance.":[13,206],"This":[14,73],"paper":[15],"shows":[16],"a":[17,34,42,110,117,136,166],"distinct":[18],"way":[19],"exploit":[21],"for":[24,55,144],"traditional":[25],"semi-supervised":[26,36],"methods,":[28],"such":[29],"as":[30,135],"self-training.":[31],"Self-training":[32],"is":[33,66,81,90,175,187],"well-known":[35],"algorithm":[38,129],"which":[39,65,115],"iteratively":[40],"trains":[41],"classifier":[43,63,80],"by":[44],"bootstrapping":[45],"from":[46,95],"data.":[48,72],"Standard":[49],"self-training":[50,93,112],"barely":[51],"selects":[52],"examples":[54,143],"training":[56,103,145,164,193],"set":[57,146],"augmentation":[58],"according":[59],"the":[61,70,78,102,122,156,162,185,192,199],"current":[62],"model,":[64],"trained":[67],"only":[68],"on":[69,170,181],"could":[74],"be":[75],"problematic":[76],"since":[77],"underlying":[79],"not":[82],"strong":[83],"enough,":[84],"especially":[85],"when":[86],"initial":[87],"sparse.":[91],"Consequently,":[92],"suffers":[94],"too":[96],"much":[97],"classification":[98,205],"noise":[99,159],"accumulated":[100],"in":[101],"set.":[104,194],"In":[105,148],"this":[106],"paper,":[107],"we":[108],"propose":[109],"novel":[111],"style":[113],"algorithm,":[114],"exploits":[116],"manifold":[118],"assumption":[119],"optimize":[121],"self-labelling":[123],"process.":[124],"Unlike":[125],"standard":[126],"self-training,":[127],"our":[128],"utilizes":[130],"whole":[137],"label":[139],"select":[141],"augmentation.":[147],"detail,":[149],"two":[150],"measures":[151],"are":[152],"employed":[153],"minimize":[155],"effect":[157],"of":[158],"introduced":[160],"set:":[165],"transductive":[167],"method":[168,201],"based":[169],"controlled":[171],"graph":[172],"random":[173],"walk":[174],"incorporated":[176],"generate":[178],"reliable":[179],"predictions":[180],"data;":[183],"secondly,":[184],"mechanism":[186],"adopted":[188],"sequentially":[190],"augment":[191],"Empirical":[195],"results":[196],"suggest":[197],"that":[198],"proposed":[200],"can":[202],"effectively":[203]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2486791387","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-03-16T14:56:56.100164","created_date":"2016-08-23"}