{"id":"https://openalex.org/W3171411176","doi":"https://doi.org/10.1142/s1469026821500139","title":"Regularized Semi-Supervised Metric Learning with Latent Structure Preserved","display_name":"Regularized Semi-Supervised Metric Learning with Latent Structure Preserved","publication_year":2021,"publication_date":"2021-06-01","ids":{"openalex":"https://openalex.org/W3171411176","doi":"https://doi.org/10.1142/s1469026821500139","mag":"3171411176"},"language":"en","primary_location":{"id":"doi:10.1142/s1469026821500139","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1469026821500139","pdf_url":null,"source":{"id":"https://openalex.org/S206936884","display_name":"International Journal of Computational Intelligence and Applications","issn_l":"1469-0268","issn":["1469-0268","1757-5885"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence and Applications","raw_type":"journal-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/A5115694806","display_name":"Qianying Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I113992204","display_name":"Hebei University of Economics and Business","ror":"https://ror.org/05j1kc284","country_code":"CN","type":"education","lineage":["https://openalex.org/I113992204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianying Wang","raw_affiliation_strings":["College of Mathematics and Statistics, Hebei University of Economics and Business, Shijiazhuang 050000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Hebei University of Economics and Business, Shijiazhuang 050000, P. R. China","institution_ids":["https://openalex.org/I113992204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102014973","display_name":"Ming Lu","orcid":"https://orcid.org/0000-0001-6174-7528"},"institutions":[{"id":"https://openalex.org/I94611258","display_name":"Hebei Normal University","ror":"https://ror.org/004rbbw49","country_code":"CN","type":"education","lineage":["https://openalex.org/I94611258"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Lu","raw_affiliation_strings":["School of Mathematical Sciences, Hebei Normal University, Shijiazhuang 050000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Hebei Normal University, Shijiazhuang 050000, P. R. China","institution_ids":["https://openalex.org/I94611258"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457569","display_name":"Meng Li","orcid":"https://orcid.org/0000-0003-3497-4391"},"institutions":[{"id":"https://openalex.org/I113992204","display_name":"Hebei University of Economics and Business","ror":"https://ror.org/05j1kc284","country_code":"CN","type":"education","lineage":["https://openalex.org/I113992204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Li","raw_affiliation_strings":["College of Mathematics and Statistics, Hebei University of Economics and Business, Shijiazhuang 050000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Hebei University of Economics and Business, Shijiazhuang 050000, P. R. China","institution_ids":["https://openalex.org/I113992204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102832461","display_name":"Fei Guan","orcid":"https://orcid.org/0000-0002-6333-2526"},"institutions":[{"id":"https://openalex.org/I113992204","display_name":"Hebei University of Economics and Business","ror":"https://ror.org/05j1kc284","country_code":"CN","type":"education","lineage":["https://openalex.org/I113992204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Guan","raw_affiliation_strings":["College of Mathematics and Statistics, Hebei University of Economics and Business, Shijiazhuang 050000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Hebei University of Economics and Business, Shijiazhuang 050000, P. R. China","institution_ids":["https://openalex.org/I113992204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102014973"],"corresponding_institution_ids":["https://openalex.org/I94611258"],"apc_list":null,"apc_paid":null,"fwci":0.097,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.37554874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"20","issue":"02","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9947999715805054,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9922999739646912,"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/discriminative-model","display_name":"Discriminative model","score":0.7647665739059448},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6820244789123535},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6639571189880371},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6346563100814819},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5961014032363892},{"id":"https://openalex.org/keywords/intrinsic-dimension","display_name":"Intrinsic dimension","score":0.5449234247207642},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5214404463768005},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5111315846443176},{"id":"https://openalex.org/keywords/large-margin-nearest-neighbor","display_name":"Large margin nearest neighbor","score":0.5049672722816467},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48927661776542664},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4776676595211029},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.47349151968955994},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4553121328353882},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.4312625527381897},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.41275712847709656},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3772677183151245},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2931230068206787},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.2342263162136078},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.1251099407672882}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7647665739059448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6820244789123535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6639571189880371},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6346563100814819},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5961014032363892},{"id":"https://openalex.org/C30732413","wikidata":"https://www.wikidata.org/wiki/Q17092636","display_name":"Intrinsic dimension","level":3,"score":0.5449234247207642},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5214404463768005},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5111315846443176},{"id":"https://openalex.org/C94475309","wikidata":"https://www.wikidata.org/wiki/Q6489154","display_name":"Large margin nearest neighbor","level":3,"score":0.5049672722816467},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48927661776542664},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4776676595211029},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.47349151968955994},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4553121328353882},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.4312625527381897},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.41275712847709656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3772677183151245},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2931230068206787},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.2342263162136078},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.1251099407672882},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1469026821500139","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1469026821500139","pdf_url":null,"source":{"id":"https://openalex.org/S206936884","display_name":"International Journal of Computational Intelligence and Applications","issn_l":"1469-0268","issn":["1469-0268","1757-5885"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G4028303502","display_name":null,"funder_award_id":"11401163","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6637032183","display_name":null,"funder_award_id":"F2019207118","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"},{"id":"https://openalex.org/G6839412744","display_name":null,"funder_award_id":"61602148","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7833195822","display_name":null,"funder_award_id":"F2017207010","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1491300635","https://openalex.org/W1742512077","https://openalex.org/W1822246767","https://openalex.org/W1977193486","https://openalex.org/W2001141328","https://openalex.org/W2047081748","https://openalex.org/W2048679005","https://openalex.org/W2053186076","https://openalex.org/W2062112832","https://openalex.org/W2065675334","https://openalex.org/W2072343647","https://openalex.org/W2101098151","https://openalex.org/W2106053110","https://openalex.org/W2116647992","https://openalex.org/W2124325819","https://openalex.org/W2129156852","https://openalex.org/W2135346934","https://openalex.org/W2136880158","https://openalex.org/W2144245116","https://openalex.org/W2163584563","https://openalex.org/W2164031334","https://openalex.org/W2807426458","https://openalex.org/W2911964244","https://openalex.org/W3022413497","https://openalex.org/W4249279051","https://openalex.org/W4302161581"],"related_works":["https://openalex.org/W2577956156","https://openalex.org/W2938226623","https://openalex.org/W2157179134","https://openalex.org/W2943682648","https://openalex.org/W2390866118","https://openalex.org/W2130532140","https://openalex.org/W2620359956","https://openalex.org/W4386450797","https://openalex.org/W1531663008","https://openalex.org/W2990663423"],"abstract_inverted_index":{"Metric":[0],"learning":[1,42],"is":[2,18,24,79,138,164],"a":[3,13,99],"critical":[4],"problem":[5],"in":[6,56,111],"classification.":[7],"Most":[8,38],"classifiers":[9],"are":[10,108],"based":[11],"on":[12,98,151,171],"metric,":[14],"the":[15,19,28,45,50,57,62,76,82,88,106,118,122,126,132,152,156,159,162,179],"simplest":[16],"one":[17],"KNN":[20],"classifier,":[21],"whose":[22],"outcome":[23],"directly":[25],"decided":[26],"by":[27,81,140],"given":[29],"metric.":[30],"This":[31],"paper":[32],"will":[33],"discuss":[34],"semi-supervised":[35,40],"metric":[36,41],"learning.":[37],"traditional":[39,180],"algorithms":[43],"preserve":[44],"local":[46,77,133],"structure":[47,78,120,137,154],"of":[48,121,155],"all":[49,87,92,105],"samples":[51,65,123],"(including":[52],"labeled":[53,64,70],"and":[54,67,103,124,144,158],"unlabeled)":[55],"input":[58],"space,":[59],"when":[60],"making":[61],"same":[63],"together":[66],"separating":[68],"different":[69],"samples.":[71,149],"In":[72],"most":[73],"existing":[74],"methods,":[75],"calculated":[80],"Euclidean":[83],"distance":[84],"which":[85],"uses":[86],"features.":[89,168],"As":[90],"we":[91,114],"know,":[93],"high":[94],"dimensional":[95],"data":[96,173],"lies":[97],"low":[100],"dimension":[101],"manifold,":[102],"not":[104],"features":[107,129],"discriminative.":[109],"Thus,":[110],"this":[112],"paper,":[113],"try":[115],"to":[116,130],"explore":[117],"latent":[119,136],"use":[125],"more":[127],"discriminative":[128],"calculate":[131],"structure.":[134],"The":[135],"learned":[139],"clustering":[141],"random":[142],"forest":[143],"cast":[145],"into":[146],"similarity":[147,163],"between":[148],"Based":[150],"hierarchical":[153],"trees":[157],"split":[160],"function,":[161],"obtained":[165],"from":[166],"discriminant":[167],"Experimental":[169],"results":[170],"public":[172],"sets":[174],"show":[175],"our":[176],"algorithm":[177],"outperforms":[178],"similar":[181],"related":[182],"algorithms.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
