{"id":"https://openalex.org/W2950811391","doi":"https://doi.org/10.3390/info10060208","title":"Latent Feature Group Learning for High-Dimensional Data Clustering","display_name":"Latent Feature Group Learning for High-Dimensional Data Clustering","publication_year":2019,"publication_date":"2019-06-10","ids":{"openalex":"https://openalex.org/W2950811391","doi":"https://doi.org/10.3390/info10060208","mag":"2950811391"},"language":"en","primary_location":{"id":"doi:10.3390/info10060208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info10060208","pdf_url":"https://www.mdpi.com/2078-2489/10/6/208/pdf?version=1561532612","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/10/6/208/pdf?version=1561532612","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017819132","display_name":"Wenting Wang","orcid":"https://orcid.org/0000-0001-5041-7988"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenting Wang","raw_affiliation_strings":["Big Data Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China","National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":"https://orcid.org/0000-0001-5041-7988","affiliations":[{"raw_affiliation_string":"Big Data Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076542236","display_name":"Yulin He","orcid":"https://orcid.org/0000-0002-3415-0686"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yulin He","raw_affiliation_strings":["Big Data Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China","National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Big Data Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049275137","display_name":"Liheng Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Liheng Ma","raw_affiliation_strings":["School of Computer Science, McGill University, Montreal, QC H3A OG4, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, McGill University, Montreal, QC H3A OG4, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003347359","display_name":"Joshua Zhexue Huang","orcid":"https://orcid.org/0000-0002-6797-2571"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Joshua Zhexue Huang","raw_affiliation_strings":["Big Data Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China","National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Big Data Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076542236"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":0.1596,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60736532,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10","issue":"6","first_page":"208","last_page":"208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9983999729156494,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9983999729156494,"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/T10057","display_name":"Face and Expression Recognition","score":0.995199978351593,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7066583633422852},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6804277300834656},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6599206924438477},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5727657079696655},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5486463308334351},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5333772897720337},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.4925876259803772},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4664686620235443},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.46568694710731506},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.42993393540382385},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39203426241874695},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.3442513942718506},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3266390562057495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20759820938110352}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7066583633422852},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6804277300834656},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6599206924438477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5727657079696655},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5486463308334351},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5333772897720337},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.4925876259803772},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4664686620235443},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.46568694710731506},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.42993393540382385},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39203426241874695},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.3442513942718506},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3266390562057495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20759820938110352},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/info10060208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info10060208","pdf_url":"https://www.mdpi.com/2078-2489/10/6/208/pdf?version=1561532612","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4a08ca4416f247499862bcd71da99676","is_oa":true,"landing_page_url":"https://doaj.org/article/4a08ca4416f247499862bcd71da99676","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 10, Iss 6, p 208 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2078-2489/10/6/208/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/info10060208","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/info10060208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info10060208","pdf_url":"https://www.mdpi.com/2078-2489/10/6/208/pdf?version=1561532612","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G427717117","display_name":null,"funder_award_id":"2016T90799","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7337711004","display_name":null,"funder_award_id":"2018060","funder_id":"https://openalex.org/F4320325571","funder_display_name":"Shenzhen University"},{"id":"https://openalex.org/G7448526600","display_name":null,"funder_award_id":"2017YFC0822604-2","funder_id":"https://openalex.org/F4320325571","funder_display_name":"Shenzhen University"}],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320325571","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2950811391.pdf","grobid_xml":"https://content.openalex.org/works/W2950811391.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W150979269","https://openalex.org/W191887720","https://openalex.org/W861238194","https://openalex.org/W1959178355","https://openalex.org/W1965070140","https://openalex.org/W1965750261","https://openalex.org/W1989946714","https://openalex.org/W2003244299","https://openalex.org/W2006533296","https://openalex.org/W2017100743","https://openalex.org/W2019403973","https://openalex.org/W2027902860","https://openalex.org/W2044080809","https://openalex.org/W2051907993","https://openalex.org/W2068640436","https://openalex.org/W2069046167","https://openalex.org/W2070150264","https://openalex.org/W2079361215","https://openalex.org/W2094909687","https://openalex.org/W2095373758","https://openalex.org/W2095512713","https://openalex.org/W2103696938","https://openalex.org/W2120887445","https://openalex.org/W2125070513","https://openalex.org/W2149707138","https://openalex.org/W2159091719","https://openalex.org/W2161985854","https://openalex.org/W2307705085","https://openalex.org/W2325846041","https://openalex.org/W2367130504","https://openalex.org/W2560528144","https://openalex.org/W2742637748","https://openalex.org/W2899610691"],"related_works":["https://openalex.org/W2014162767","https://openalex.org/W2809283963","https://openalex.org/W2367260997","https://openalex.org/W2115729582","https://openalex.org/W2363406585","https://openalex.org/W2106492215","https://openalex.org/W2326694407","https://openalex.org/W2082859007","https://openalex.org/W2378719652","https://openalex.org/W2164831575"],"abstract_inverted_index":{"In":[0,45,162],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,132],"latent":[6],"feature":[7,15,25,58,71,87,108,127,142],"group":[8],"learning":[9],"(LFGL)":[10],"algorithm":[11,75,170],"to":[12,54,82,154],"discover":[13],"the":[14,37,48,56,67,79,84,98,106,115,121,126,138,156,165,181],"grouping":[16,26,59,72,88,109],"structures":[17,89],"and":[18,39,125,150],"subspace":[19],"clusters":[20,102],"for":[21,159],"high-dimensional":[22,42,104,188],"data.":[23,189],"The":[24,70,145],"structures,":[27,60],"which":[28,61,179],"are":[29,62,129,152],"learned":[30],"in":[31,66,90,103],"an":[32],"analytical":[33],"way,":[34],"can":[35],"enhance":[36],"accuracy":[38],"efficiency":[40],"of":[41,93,101,141,148,184],"data":[43],"clustering.":[44],"LFGL":[46,169,185],"algorithm,":[47],"Darwinian":[49],"evolutionary":[50],"process":[51],"is":[52,76,112],"used":[53,77,153],"explore":[55],"optimal":[57],"coded":[63],"as":[64,78,131],"chromosomes":[65,85,158],"genetic":[68,146],"algorithm.":[69],"weighting":[73,110],"k-means":[74,111],"fitness":[80],"function":[81],"evaluate":[83],"or":[86],"each":[91],"generation":[92],"evolution.":[94],"To":[95],"better":[96,182],"handle":[97],"diverse":[99],"densities":[100],"data,":[105],"original":[107],"revised":[113],"with":[114,164],"mass-based":[116],"dissimilarity":[117],"measure":[118,124],"rather":[119],"than":[120],"Euclidean":[122],"distance":[123],"weights":[128],"optimized":[130],"nonnegative":[133],"matrix":[134],"factorization":[135],"problem":[136],"under":[137],"orthogonal":[139],"constraint":[140],"weight":[143],"matrix.":[144],"operations":[147],"mutation":[149],"crossover":[151],"generate":[155],"new":[157],"next":[160],"generation.":[161],"comparison":[163],"well-known":[166],"clustering":[167,187],"algorithms,":[168],"produced":[171],"encouraging":[172],"experimental":[173],"results":[174],"on":[175],"real":[176],"world":[177],"datasets,":[178],"demonstrated":[180],"performance":[183],"when":[186]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}