{"id":"https://openalex.org/W2615068864","doi":"https://doi.org/10.1109/tnnls.2017.2699674","title":"An Information-Theoretic-Cluster Visualization for Self-Organizing Maps","display_name":"An Information-Theoretic-Cluster Visualization for Self-Organizing Maps","publication_year":2017,"publication_date":"2017-05-17","ids":{"openalex":"https://openalex.org/W2615068864","doi":"https://doi.org/10.1109/tnnls.2017.2699674","mag":"2615068864","pmid":"https://pubmed.ncbi.nlm.nih.gov/28534793"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2017.2699674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2699674","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5012478671","display_name":"Leonardo Enzo Brito da Silva","orcid":"https://orcid.org/0000-0003-3639-9175"},"institutions":[{"id":"https://openalex.org/I1293487690","display_name":"Ministry of Education","ror":"https://ror.org/04d0xx942","country_code":"BR","type":"government","lineage":["https://openalex.org/I1293487690","https://openalex.org/I2801200668"]},{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]},{"id":"https://openalex.org/I4210097716","display_name":"Coordena\u00e7\u00e3o de Aperfeicoamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614","country_code":"BR","type":"government","lineage":["https://openalex.org/I1293487690","https://openalex.org/I2801200668","https://openalex.org/I4210097716"]}],"countries":["BR","US"],"is_corresponding":false,"raw_author_name":"Leonardo Enzo Brito da Silva","raw_affiliation_strings":["Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO, USA","CAPES Foundation, Ministry of Education of Brazil, Bras\u00edlia, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-3639-9175","affiliations":[{"raw_affiliation_string":"Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]},{"raw_affiliation_string":"CAPES Foundation, Ministry of Education of Brazil, Bras\u00edlia, Brazil","institution_ids":["https://openalex.org/I1293487690","https://openalex.org/I4210097716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038037619","display_name":"Donald C. Wunsch","orcid":"https://orcid.org/0000-0002-9726-9051"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donald C. Wunsch","raw_affiliation_strings":["Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":3.6502,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.94049815,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"29","issue":"6","first_page":"2595","last_page":"2613"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994000196456909,"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/T10320","display_name":"Neural Networks and Applications","score":0.9994000196456909,"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":0.9793000221252441,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9764000177383423,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7691054344177246},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6931765079498291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6747964024543762},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.564264714717865},{"id":"https://openalex.org/keywords/distance-matrix","display_name":"Distance matrix","score":0.5252661108970642},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.5112922191619873},{"id":"https://openalex.org/keywords/parallel-coordinates","display_name":"Parallel coordinates","score":0.4409497380256653},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.42937400937080383},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4262537360191345},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4206128418445587},{"id":"https://openalex.org/keywords/fisher-kernel","display_name":"Fisher kernel","score":0.41878557205200195},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.40258777141571045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3473801016807556},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2802632451057434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2425672709941864}],"concepts":[{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7691054344177246},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6931765079498291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6747964024543762},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.564264714717865},{"id":"https://openalex.org/C111208986","wikidata":"https://www.wikidata.org/wiki/Q901698","display_name":"Distance matrix","level":2,"score":0.5252661108970642},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.5112922191619873},{"id":"https://openalex.org/C60011546","wikidata":"https://www.wikidata.org/wiki/Q932996","display_name":"Parallel coordinates","level":4,"score":0.4409497380256653},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.42937400937080383},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4262537360191345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4206128418445587},{"id":"https://openalex.org/C207798031","wikidata":"https://www.wikidata.org/wiki/Q8563425","display_name":"Fisher kernel","level":5,"score":0.41878557205200195},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.40258777141571045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3473801016807556},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2802632451057434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2425672709941864},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.0},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2017.2699674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2699674","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:28534793","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28534793","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7072744559","display_name":null,"funder_award_id":"BEX 13494/13-9","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":86,"referenced_works":["https://openalex.org/W17418856","https://openalex.org/W45590150","https://openalex.org/W65738273","https://openalex.org/W183111108","https://openalex.org/W1175789168","https://openalex.org/W1518498072","https://openalex.org/W1520723760","https://openalex.org/W1541565701","https://openalex.org/W1545908348","https://openalex.org/W1564419782","https://openalex.org/W1841961408","https://openalex.org/W1953385699","https://openalex.org/W1972098431","https://openalex.org/W1972848503","https://openalex.org/W1972969203","https://openalex.org/W1989249416","https://openalex.org/W1994008698","https://openalex.org/W1994409504","https://openalex.org/W2001619934","https://openalex.org/W2009581456","https://openalex.org/W2011599294","https://openalex.org/W2019359195","https://openalex.org/W2025649768","https://openalex.org/W2025818287","https://openalex.org/W2027653851","https://openalex.org/W2047870719","https://openalex.org/W2048365415","https://openalex.org/W2057041027","https://openalex.org/W2059619493","https://openalex.org/W2066226535","https://openalex.org/W2079682462","https://openalex.org/W2079810998","https://openalex.org/W2083085790","https://openalex.org/W2088709281","https://openalex.org/W2093358140","https://openalex.org/W2100005846","https://openalex.org/W2101938621","https://openalex.org/W2103137709","https://openalex.org/W2107317146","https://openalex.org/W2107402227","https://openalex.org/W2108122721","https://openalex.org/W2110802877","https://openalex.org/W2122389322","https://openalex.org/W2122882636","https://openalex.org/W2124592110","https://openalex.org/W2125236599","https://openalex.org/W2125464731","https://openalex.org/W2125478079","https://openalex.org/W2127218421","https://openalex.org/W2127247753","https://openalex.org/W2131838522","https://openalex.org/W2132377940","https://openalex.org/W2133059825","https://openalex.org/W2134312057","https://openalex.org/W2135160607","https://openalex.org/W2135964318","https://openalex.org/W2142363274","https://openalex.org/W2153233077","https://openalex.org/W2155903894","https://openalex.org/W2155936364","https://openalex.org/W2158436185","https://openalex.org/W2162506329","https://openalex.org/W2164177061","https://openalex.org/W2169044495","https://openalex.org/W2169838897","https://openalex.org/W2170590171","https://openalex.org/W2171731854","https://openalex.org/W2295256067","https://openalex.org/W2538115256","https://openalex.org/W2615090770","https://openalex.org/W3023708208","https://openalex.org/W3036846224","https://openalex.org/W3120740533","https://openalex.org/W3152290665","https://openalex.org/W4205687621","https://openalex.org/W4213009331","https://openalex.org/W4230367971","https://openalex.org/W4235169531","https://openalex.org/W4244003036","https://openalex.org/W4245176872","https://openalex.org/W4251002338","https://openalex.org/W6600691717","https://openalex.org/W6630985644","https://openalex.org/W6676978831","https://openalex.org/W6678534278","https://openalex.org/W6678914141"],"related_works":["https://openalex.org/W2770767919","https://openalex.org/W2070275453","https://openalex.org/W1983314790","https://openalex.org/W2116732611","https://openalex.org/W2093133953","https://openalex.org/W2059973664","https://openalex.org/W2015073373","https://openalex.org/W1966389922","https://openalex.org/W2087856434","https://openalex.org/W4247097485"],"abstract_inverted_index":{"Improved":[0],"data":[1,69,134,169],"visualization":[2,20,29,161],"will":[3],"be":[4],"a":[5,138,176],"significant":[6,177],"tool":[7],"to":[8,91,100,142,201],"enhance":[9],"cluster":[10,19,185,190],"analysis.":[11],"In":[12],"this":[13,172,220],"paper,":[14,221],"an":[15,64,144],"information-theoretic-based":[16],"method":[17],"for":[18,163,222],"using":[21,232],"self-organizing":[22],"maps":[23],"(SOMs)":[24],"is":[25,154],"presented.":[26],"The":[27,116,148,180],"information-theoretic":[28,197],"(IT-vis)":[30],"has":[31,63],"the":[32,36,51,54,68,74,77,82,102,120,129,133,152,183,196,205,216,224,227],"same":[33],"structure":[34,135],"as":[35],"unified":[37],"distance":[38],"matrix,":[39],"but":[40],"instead":[41],"of":[42,67,76,128,137,151,204,212,226],"depicting":[43],"Euclidean":[44],"distances":[45],"between":[46,53],"adjacent":[47,58],"neurons,":[48],"it":[49,158],"displays":[50],"similarity":[52,103],"distributions":[55],"associated":[56,65],"with":[57,80,159,208],"neurons.":[59],"Each":[60],"SOM":[61],"neuron":[62],"subset":[66],"set":[70],"whose":[71],"cardinality":[72],"controls":[73],"granularity":[75],"IT-vis":[78,153,184,211],"and":[79,84,89,111,124,132,166],"which":[81,189,223],"first-":[83],"second-order":[85],"statistics":[86],"are":[87,98,192,199],"computed":[88],"used":[90,99,200],"estimate":[92],"their":[93],"probability":[94],"density":[95],"functions.":[96],"These":[97],"calculate":[101],"measure,":[104],"based":[105],"on":[106],"Renyi's":[107],"quadratic":[108],"cross":[109,112],"entropy":[110],"information":[113],"potential":[114],"(CIP).":[115],"introduced":[117],"visualizations":[118,198],"combine":[119],"low":[121],"computational":[122],"cost":[123],"kernel":[125],"estimation":[126],"properties":[127],"representative":[130],"CIP":[131],"representation":[136],"single-linkage-based":[139],"grouping":[140],"algorithm":[141],"generate":[143],"enhanced":[145],"SOM-based":[146],"visualization.":[147],"visual":[149],"quality":[150,225],"assessed":[155],"by":[156],"comparing":[157],"other":[160,209],"methods":[162],"several":[164],"real-world":[165],"synthetic":[167],"benchmark":[168],"sets.":[170],"Thus,":[171],"paper":[173],"also":[174],"contains":[175],"literature":[178],"survey.":[179],"experiments":[181],"demonstrate":[182],"revealing":[186],"capabilities,":[187],"in":[188,219],"boundaries":[191],"sharply":[193],"captured.":[194],"Additionally,":[195],"perform":[202],"clustering":[203],"SOM.":[206],"Compared":[207],"methods,":[210],"large":[213],"SOMs":[214],"yielded":[215],"best":[217],"results":[218],"final":[228],"partitions":[229],"was":[230],"evaluated":[231],"external":[233],"validity":[234],"indices.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}