{"id":"https://openalex.org/W2810097382","doi":"https://doi.org/10.1080/08839514.2018.1486129","title":"Mutual neighbors and diagonal loading-based sparse locally linear embedding","display_name":"Mutual neighbors and diagonal loading-based sparse locally linear embedding","publication_year":2018,"publication_date":"2018-05-28","ids":{"openalex":"https://openalex.org/W2810097382","doi":"https://doi.org/10.1080/08839514.2018.1486129","mag":"2810097382"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2018.1486129","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2018.1486129","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5017275529","display_name":"Rassoul Hajizadeh","orcid":"https://orcid.org/0000-0002-8570-1492"},"institutions":[{"id":"https://openalex.org/I84248293","display_name":"Babol Noshirvani University of Technology","ror":"https://ror.org/02zc85170","country_code":"IR","type":"education","lineage":["https://openalex.org/I84248293"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Rassoul Hajizadeh","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran","institution_ids":["https://openalex.org/I84248293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027961566","display_name":"Ali Aghagolzadeh","orcid":"https://orcid.org/0000-0002-6999-3464"},"institutions":[{"id":"https://openalex.org/I84248293","display_name":"Babol Noshirvani University of Technology","ror":"https://ror.org/02zc85170","country_code":"IR","type":"education","lineage":["https://openalex.org/I84248293"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Ali Aghagolzadeh","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran","institution_ids":["https://openalex.org/I84248293"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084472595","display_name":"Mehdi Ezoji","orcid":"https://orcid.org/0000-0003-0471-4396"},"institutions":[{"id":"https://openalex.org/I84248293","display_name":"Babol Noshirvani University of Technology","ror":"https://ror.org/02zc85170","country_code":"IR","type":"education","lineage":["https://openalex.org/I84248293"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mehdi Ezoji","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran","institution_ids":["https://openalex.org/I84248293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027961566"],"corresponding_institution_ids":["https://openalex.org/I84248293"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.06059741,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"32","issue":"5","first_page":"496","last_page":"514"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9699000120162964,"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":0.9699000120162964,"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/T10205","display_name":"Advanced Fiber Optic Sensors","score":0.9642000198364258,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/diagonal","display_name":"Diagonal","score":0.6774760484695435},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5758057832717896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5649363994598389},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5276868343353271},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4913271963596344},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.47575706243515015},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4751862585544586},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.45315974950790405},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.44549161195755005},{"id":"https://openalex.org/keywords/main-diagonal","display_name":"Main diagonal","score":0.43256238102912903},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4321584105491638},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.425855427980423},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4254826009273529},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.42385134100914},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42158299684524536},{"id":"https://openalex.org/keywords/distance-matrix","display_name":"Distance matrix","score":0.4203430414199829},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3774828612804413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3671758770942688},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22506394982337952},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.17703798413276672},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0938156247138977}],"concepts":[{"id":"https://openalex.org/C130367717","wikidata":"https://www.wikidata.org/wiki/Q189791","display_name":"Diagonal","level":2,"score":0.6774760484695435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5758057832717896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5649363994598389},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5276868343353271},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4913271963596344},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.47575706243515015},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4751862585544586},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.45315974950790405},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.44549161195755005},{"id":"https://openalex.org/C60761296","wikidata":"https://www.wikidata.org/wiki/Q651480","display_name":"Main diagonal","level":3,"score":0.43256238102912903},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4321584105491638},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.425855427980423},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4254826009273529},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.42385134100914},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42158299684524536},{"id":"https://openalex.org/C111208986","wikidata":"https://www.wikidata.org/wiki/Q901698","display_name":"Distance matrix","level":2,"score":0.4203430414199829},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3774828612804413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3671758770942688},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22506394982337952},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.17703798413276672},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0938156247138977},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2018.1486129","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2018.1486129","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c6b5f2992e7b495d9849ed17c645916b","is_oa":false,"landing_page_url":"https://doaj.org/article/c6b5f2992e7b495d9849ed17c645916b","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 32, Iss 5, Pp 496-514 (2018)","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1991078647","https://openalex.org/W2001141328","https://openalex.org/W2053186076","https://openalex.org/W2077776048","https://openalex.org/W2156838815","https://openalex.org/W2168854967","https://openalex.org/W2479500547","https://openalex.org/W2528566462","https://openalex.org/W2531288459","https://openalex.org/W3144619878","https://openalex.org/W4212805869","https://openalex.org/W4250689175","https://openalex.org/W4250857377","https://openalex.org/W4377043424"],"related_works":["https://openalex.org/W2001076853","https://openalex.org/W4280529579","https://openalex.org/W1605858995","https://openalex.org/W2146092900","https://openalex.org/W2129007136","https://openalex.org/W4200515925","https://openalex.org/W2883186538","https://openalex.org/W2084734121","https://openalex.org/W2137165282","https://openalex.org/W2742332863"],"abstract_inverted_index":{"In":[0,51],"this":[1,52],"study,":[2,53],"a":[3,36],"new":[4],"Locally":[5],"Linear":[6],"Embedding":[7],"(LLE)":[8],"algorithm":[9],"is":[10,29,40,87,101],"proposed.":[11],"Common":[12],"LLE":[13],"includes":[14],"three":[15],"steps.":[16],"First,":[17],"neighbors":[18,34],"of":[19,85,91,96,113,124,138,151],"each":[20,26,55,84],"data":[21,27,44,56,76],"point":[22,28,57],"are":[23,45,67],"determined.":[24],"Second,":[25],"linearly":[30],"modeled":[31],"using":[32,47],"its":[33,63,105],"and":[35,61,107,129,132,167],"similarity":[37],"graph":[38,49],"matrix":[39,65,100],"constructed.":[41],"Third,":[42],"embedded":[43],"extracted":[46],"the":[48,71,89,92,97,111,116,122,136,140,148,152],"matrix.":[50],"for":[54],"mutual":[58,81,126,141],"neighborhood":[59,90,127,142],"conception":[60,128],"loading":[62,95,131],"covariance":[64,99],"diagonally":[66],"used":[68],"to":[69,103,109],"calculate":[70],"linear":[72],"modeling":[73],"coefficients.":[74,118],"Two":[75],"points":[77],"will":[78],"be":[79],"named":[80],"neighbors,":[82],"if":[83],"them":[86],"in":[88,115],"other.":[93],"Diagonal":[94],"neighboring":[98],"applied":[102],"avoid":[104],"singularity":[106],"also":[108],"diminish":[110],"effect":[112],"noise":[114],"reconstruction":[117],"Simulation":[119],"results":[120,137],"demonstrate":[121,147],"performance":[123,150],"applying":[125,139],"diagonal":[130],"their":[133],"combination.":[134],"Also,":[135],"on":[143,163],"Laplacian":[144],"Eigenmap":[145],"(LEM)":[146],"good":[149],"proposed":[153,158],"neighbor":[154],"selection":[155],"method.":[156],"Our":[157],"method":[159],"improves":[160],"recognition":[161],"rate":[162],"Persian":[164],"handwritten":[165],"digits":[166],"face":[168],"image":[169],"databases.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}