{"id":"https://openalex.org/W2783104335","doi":"https://doi.org/10.1109/iske.2017.8258775","title":"Label-expanded manifold regularization for semi-supervised classification","display_name":"Label-expanded manifold regularization for semi-supervised classification","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2783104335","doi":"https://doi.org/10.1109/iske.2017.8258775","mag":"2783104335"},"language":"en","primary_location":{"id":"doi:10.1109/iske.2017.8258775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2017.8258775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","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/A5083243931","display_name":"Yating Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yating Shen","raw_affiliation_strings":["Nanjing University of Posts and Telicommunications, Nanjing, Jiangsu Province"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telicommunications, Nanjing, Jiangsu Province","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100714799","display_name":"Yunyun Wang","orcid":"https://orcid.org/0000-0002-5884-9408"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunyun Wang","raw_affiliation_strings":["Nanjing University of Posts and Telicommunications, Nanjing, Jiangsu Province"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telicommunications, Nanjing, Jiangsu Province","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045463943","display_name":"Zhiguo Ma","orcid":"https://orcid.org/0009-0001-7801-4504"},"institutions":[{"id":"https://openalex.org/I4210161138","display_name":"Beijing Fengtai Hospital","ror":"https://ror.org/0579e9266","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiguo Ma","raw_affiliation_strings":["Fengtai District, Beijing Electric-machine Institution, Beijing City"],"affiliations":[{"raw_affiliation_string":"Fengtai District, Beijing Electric-machine Institution, Beijing City","institution_ids":["https://openalex.org/I4210161138"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083243931"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50022254,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"41","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.988099992275238,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.6900444626808167},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6545068621635437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6364544034004211},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6336531639099121},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.5360375642776489},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5024809837341309},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4420498013496399},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.437557578086853},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.4147694408893585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41409018635749817},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.39210131764411926},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32782822847366333},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.11596810817718506},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08850705623626709}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6900444626808167},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6545068621635437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6364544034004211},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6336531639099121},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.5360375642776489},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5024809837341309},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4420498013496399},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.437557578086853},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.4147694408893585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41409018635749817},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.39210131764411926},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32782822847366333},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.11596810817718506},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08850705623626709},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske.2017.8258775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2017.8258775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1541811775","https://openalex.org/W1985583020","https://openalex.org/W1990334093","https://openalex.org/W2003649494","https://openalex.org/W2020431774","https://openalex.org/W2029450386","https://openalex.org/W2035435035","https://openalex.org/W2068927523","https://openalex.org/W2104290444","https://openalex.org/W2134284153","https://openalex.org/W2997701990","https://openalex.org/W4210997624","https://openalex.org/W6675747103","https://openalex.org/W6680088802"],"related_works":["https://openalex.org/W2387045723","https://openalex.org/W2375518579","https://openalex.org/W117517268","https://openalex.org/W2944373987","https://openalex.org/W65619410","https://openalex.org/W2112684860","https://openalex.org/W2391701611","https://openalex.org/W2149544245","https://openalex.org/W3109610583","https://openalex.org/W2153107493"],"abstract_inverted_index":{"Manifold":[0],"regularization":[1],"(MR)":[2],"provides":[3],"a":[4,60,73],"powerful":[5],"framework":[6,64],"for":[7,66,68],"semi-supervised":[8,69,121],"classification,":[9],"which":[10],"propagates":[11],"labels":[12],"from":[13,39],"the":[14,25,47,84,90,100,107],"labeled":[15,32,108],"instances":[16,23,33,41,88,97,109],"to":[17,42,82,105,119],"unlabeled":[18],"ones":[19],"so":[20],"that":[21,113],"similar":[22,28],"over":[24],"manifold":[26],"have":[27],"classification":[29,48,122],"outputs.":[30],"However,":[31],"are":[34,103],"randomly":[35],"located.":[36],"Label":[37],"propagation":[38],"those":[40,96],"their":[43],"neighbors":[44],"may":[45],"mislead":[46],"of":[49,93],"MR.":[50],"To":[51],"address":[52],"this":[53,56],"issue,":[54],"in":[55,89],"paper":[57],"we":[58],"develop":[59],"novel":[61],"label-expanded":[62],"MR":[63],"(LE_MR":[65],"short)":[67],"classification.":[70],"In":[71],"LE_MR,":[72],"clustering":[74],"strategy":[75],"such":[76],"as":[77],"KFCM":[78],"is":[79],"first":[80],"adopted":[81,104],"discover":[83],"high-confidence":[85],"instances,":[86],"i.e.,":[87],"central":[91],"region":[92],"clusters.":[94],"Then":[95],"along":[98],"with":[99],"cluster":[101],"indices":[102],"expand":[106],"set.":[110],"Experiments":[111],"show":[112],"LE_MR":[114],"obtains":[115],"encouraging":[116],"results":[117],"compared":[118],"state-of-the-art":[120],"methods.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
