{"id":"https://openalex.org/W1838385076","doi":"https://doi.org/10.1109/ijcnn.2003.1223687","title":"Unsupervised similarity-based feature selection using heuristic Hopfield neural networks","display_name":"Unsupervised similarity-based feature selection using heuristic Hopfield neural networks","publication_year":2004,"publication_date":"2004-03-22","ids":{"openalex":"https://openalex.org/W1838385076","doi":"https://doi.org/10.1109/ijcnn.2003.1223687","mag":"1838385076"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2003.1223687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","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/A5087205364","display_name":"Shengping Shi","orcid":"https://orcid.org/0009-0009-1146-9158"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"S.Y.M. Shi","raw_affiliation_strings":["School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore","Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ, Singapore#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ, Singapore#TAB#","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025626208","display_name":"Ponnuthurai Nagaratnam Suganthan","orcid":"https://orcid.org/0000-0003-0901-5105"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"P.N. Suganthan","raw_affiliation_strings":["School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore","Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ, Singapore#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ, Singapore#TAB#","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087205364"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.07712735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1838","last_page":"1843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9902999997138977,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9690999984741211,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.663208544254303},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6511375904083252},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6416090130805969},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5820059776306152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5781709551811218},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5435769557952881},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5206046104431152},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5087831616401672},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.46442925930023193},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4377765655517578},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.431514710187912},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3621090054512024}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.663208544254303},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6511375904083252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6416090130805969},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5820059776306152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5781709551811218},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5435769557952881},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5206046104431152},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5087831616401672},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.46442925930023193},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4377765655517578},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.431514710187912},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3621090054512024},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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:10.1109/ijcnn.2003.1223687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W107417804","https://openalex.org/W138217685","https://openalex.org/W1497468158","https://openalex.org/W1553244859","https://openalex.org/W1597286183","https://openalex.org/W1619226191","https://openalex.org/W1819745531","https://openalex.org/W2002844845","https://openalex.org/W2010863474","https://openalex.org/W2017337590","https://openalex.org/W2026535637","https://openalex.org/W2040884411","https://openalex.org/W2041326400","https://openalex.org/W2060542593","https://openalex.org/W2113890143","https://openalex.org/W2133462743","https://openalex.org/W2136087206","https://openalex.org/W2147760898","https://openalex.org/W2148633389","https://openalex.org/W2149772057","https://openalex.org/W2154805642","https://openalex.org/W2159537329","https://openalex.org/W6604381419"],"related_works":["https://openalex.org/W3176621072","https://openalex.org/W1495042958","https://openalex.org/W2494338568","https://openalex.org/W2995475466","https://openalex.org/W2122678784","https://openalex.org/W2356785732","https://openalex.org/W2282510344","https://openalex.org/W2156571267","https://openalex.org/W20047544","https://openalex.org/W2747166117"],"abstract_inverted_index":{"An":[0],"unsupervised":[1,125],"similarity-based":[2],"feature":[3,25,45,55,110,135,138],"selection":[4,26,46,56,136],"approach":[5,128],"using":[6],"heuristic":[7],"Hopfield":[8,62],"neural":[9],"networks":[10],"(UFS-HHNN)":[11],"is":[12,21,39,81,92],"presented.":[13],"The":[14],"key":[15],"novel":[16],"ingredient":[17],"of":[18,36,74],"the":[19,24,40,54,72,79,88,122],"algorithm":[20],"to":[22,58,83,133],"formulate":[23],"problem":[27,57],"as":[28,47,94],"a":[29,48,59,84,95],"combinatorial":[30,49],"optimization":[31,50],"problem.":[32,51],"To":[33],"our":[34],"best":[35,89],"knowledge,":[37],"this":[38],"first":[41],"attempt":[42],"at":[43],"formulating":[44],"We":[52],"map":[53],"single":[60],"layered":[61],"Networks":[63],"and":[64,106,137],"adjust":[65],"parameters.":[66],"Maximum":[67],"Information":[68],"Compression":[69],"Index":[70],"(MICI),":[71],"amount":[73],"reconstruction":[75],"error":[76],"committed":[77],"if":[78],"data":[80],"projected":[82],"reduced":[85],"dimension":[86],"in":[87],"possible":[90],"way,":[91],"employed":[93],"similarity":[96],"measure.":[97],"Simulation":[98],"on":[99],"eight":[100],"benchmark":[101],"datasets":[102],"with":[103,112],"different":[104],"dimensions":[105],"size":[107],"shows":[108],"that":[109],"subsets":[111],"much":[113],"lower":[114],"redundancy":[115],"are":[116],"achieved":[117],"by":[118],"UFS/spl":[119],"I.bar/HHNN":[120],"than":[121],"recently":[123],"developed":[124],"algorithm.":[126],"Our":[127],"can":[129],"be":[130],"easily":[131],"extended":[132],"supervised":[134],"scaling.":[139]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}