{"id":"https://openalex.org/W4360605002","doi":"https://doi.org/10.1109/icnc57223.2023.10074296","title":"Wrapper-Based Federated Feature Selection for IoT Environments","display_name":"Wrapper-Based Federated Feature Selection for IoT Environments","publication_year":2023,"publication_date":"2023-02-20","ids":{"openalex":"https://openalex.org/W4360605002","doi":"https://doi.org/10.1109/icnc57223.2023.10074296"},"language":"en","primary_location":{"id":"doi:10.1109/icnc57223.2023.10074296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc57223.2023.10074296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Computing, Networking and Communications (ICNC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5054739333","display_name":"Afsaneh Mahanipour","orcid":null},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Afsaneh Mahanipour","raw_affiliation_strings":["University of Kentucky,Department of Computer Science,Lexington,KY,USA","Department of Computer Science, University of Kentucky, Lexington, KY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kentucky,Department of Computer Science,Lexington,KY,USA","institution_ids":["https://openalex.org/I143302722"]},{"raw_affiliation_string":"Department of Computer Science, University of Kentucky, Lexington, KY, USA","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080827772","display_name":"Hana Khamfroush","orcid":"https://orcid.org/0000-0002-4859-814X"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hana Khamfroush","raw_affiliation_strings":["University of Kentucky,Department of Computer Science,Lexington,KY,USA","Department of Computer Science, University of Kentucky, Lexington, KY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kentucky,Department of Computer Science,Lexington,KY,USA","institution_ids":["https://openalex.org/I143302722"]},{"raw_affiliation_string":"Department of Computer Science, University of Kentucky, Lexington, KY, USA","institution_ids":["https://openalex.org/I143302722"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143302722"],"apc_list":null,"apc_paid":null,"fwci":5.6931,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.97329937,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"214","last_page":"219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9959999918937683,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9959999918937683,"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"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9954000115394592,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9925000071525574,"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/mnist-database","display_name":"MNIST database","score":0.8969467282295227},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.804764986038208},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.756344735622406},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.6890882849693298},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6221988797187805},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.561337411403656},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.559026300907135},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.513009250164032},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5124438405036926},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4440922141075134},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4415777623653412},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.421661376953125},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.32848337292671204},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.22023451328277588},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.17197400331497192}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8969467282295227},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.804764986038208},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.756344735622406},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.6890882849693298},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6221988797187805},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.561337411403656},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.559026300907135},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.513009250164032},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5124438405036926},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4440922141075134},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4415777623653412},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.421661376953125},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.32848337292671204},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.22023451328277588},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.17197400331497192},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc57223.2023.10074296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc57223.2023.10074296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Computing, Networking and Communications (ICNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2055631528","https://openalex.org/W2072955302","https://openalex.org/W2113890143","https://openalex.org/W2530417694","https://openalex.org/W2798720628","https://openalex.org/W2849342073","https://openalex.org/W2966868966","https://openalex.org/W3021654819","https://openalex.org/W3048916457","https://openalex.org/W3105122387","https://openalex.org/W3127432888","https://openalex.org/W3199488740","https://openalex.org/W4210276279"],"related_works":["https://openalex.org/W2950475743","https://openalex.org/W4386603768","https://openalex.org/W2886711096","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W2590796488","https://openalex.org/W4389249638","https://openalex.org/W2734358244","https://openalex.org/W4388700941","https://openalex.org/W3015200942"],"abstract_inverted_index":{"Novel":[0],"Internet":[1],"of":[2,78,90,167,206,217],"Things":[3],"(IoT)":[4],"applications":[5],"have":[6],"emerged":[7],"as":[8,48,71,73,239,241],"enabling":[9],"technologies":[10],"for":[11,37,102,110],"the":[12,29,64,68,75,79,86,95,99,114,135,195,215,218],"smart":[13],"city":[14],"initiative.":[15],"IoT":[16,130],"devices":[17,131],"collect":[18],"or":[19,31,55],"produce":[20],"huge":[21],"multi-modal":[22],"data":[23,41,91,111,143,186],"that":[24,194],"is":[25,83,127],"either":[26],"processed":[27],"on":[28,184],"edge":[30],"sent":[32],"to":[33,51,84,98,107,113,133,161,233],"a":[34,119,156,163,223,242],"central":[35],"cloud":[36],"processing.":[38,104],"The":[39,81,145,211],"collected":[40],"sets":[42,187],"are":[43],"pre-processed":[44],"by":[45,67],"methods":[46,238],"known":[47],"\u201cfeature":[49],"selection\u201d,":[50],"remove":[52,202],"redundant,":[53],"irrelevant,":[54],"noisy":[56],"features.":[57],"Feature":[58],"selection":[59,124,237,244],"will":[60],"help":[61],"with":[62],"improving":[63],"results":[65,183,213],"achieved":[66],"learning":[69,179],"method":[70,198,220],"well":[72,240],"reducing":[74],"computational":[76],"complexity":[77],"model.":[80],"goal":[82],"select":[85,134,162],"most":[87,136],"informative":[88,137,168],"features":[89,97,138,207],"and":[92,158,170,178,191,228],"only":[93],"transmit":[94],"selected":[96],"edge/cloud":[100],"servers":[101],"further":[103],"This":[105],"leads":[106],"smaller":[108],"costs":[109],"transmission":[112],"servers.":[115],"In":[116],"this":[117],"paper,":[118],"novel":[120],"wrapper-based":[121],"federated":[122,157],"feature":[123,236],"(FFS)":[125],"algorithm":[126,148,153],"proposed,":[128],"where":[129],"collaborate":[132],"without":[139,208],"sharing":[140],"their":[141],"local":[142],"sets.":[144],"proposed":[146,196,219],"FFS":[147],"uses":[149],"binary":[150],"gravitational":[151],"search":[152],"(BGSA)":[154],"in":[155,200,221,231],"collaborative":[159],"manner":[160],"small":[164],"enough":[165],"subset":[166],"attributes":[169],"provide":[171],"an":[172],"improved":[173],"trade-off":[174,225],"between":[175,226],"communication":[176,229],"cost":[177,230],"accuracy.":[180],"Our":[181],"experimental":[182],"three":[185],"including":[188],"MNIST,":[189],"Fashion-MNIST,":[190],"MAV":[192],"demonstrate":[193],"BGSAFFS":[197],"can":[199],"average":[201],"more":[203],"than":[204],"50%":[205],"losing":[209],"information.":[210],"obtained":[212],"prove":[214],"effectiveness":[216],"achieving":[222],"good":[224],"accuracy":[227],"comparison":[232],"other":[234],"state-of-the-art":[235],"no-feature":[243],"baseline.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-10-10T00:00:00"}
