{"id":"https://openalex.org/W4392085048","doi":"https://doi.org/10.1109/tsp.2024.3368769","title":"Constructing Indoor Region-Based Radio Map Without Location Labels","display_name":"Constructing Indoor Region-Based Radio Map Without Location Labels","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4392085048","doi":"https://doi.org/10.1109/tsp.2024.3368769"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2024.3368769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3368769","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-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/A5036659144","display_name":"Zheng Xing","orcid":"https://orcid.org/0000-0002-9710-082X"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zheng Xing","raw_affiliation_strings":["School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, China","School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101802022","display_name":"Junting Chen","orcid":"https://orcid.org/0000-0003-3056-9030"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junting Chen","raw_affiliation_strings":["School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, China","School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"School of Science and Engineering, and the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036659144"],"corresponding_institution_ids":["https://openalex.org/I4210116924"],"apc_list":null,"apc_paid":null,"fwci":3.4911,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.92920368,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"2512","last_page":"2526"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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":1.0,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10860","display_name":"Speech and Audio Processing","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/rss","display_name":"RSS","score":0.8756052255630493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7598028182983398},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6853605508804321},{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.6468927264213562},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.5718350410461426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4839242100715637},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4760282337665558},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4571797847747803},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4411745071411133},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.42775362730026245},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.13482996821403503}],"concepts":[{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.8756052255630493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598028182983398},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6853605508804321},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.6468927264213562},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.5718350410461426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4839242100715637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4760282337665558},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4571797847747803},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4411745071411133},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.42775362730026245},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.13482996821403503},{"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/tsp.2024.3368769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3368769","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G5765647807","display_name":null,"funder_award_id":"2018YFB1800800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6352250275","display_name":null,"funder_award_id":"62293482","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6671230061","display_name":null,"funder_award_id":"62171398","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1460189015","https://openalex.org/W2103542269","https://openalex.org/W2116324873","https://openalex.org/W2129736664","https://openalex.org/W2135394914","https://openalex.org/W2146610201","https://openalex.org/W2342539491","https://openalex.org/W2770771835","https://openalex.org/W2791801566","https://openalex.org/W2886915282","https://openalex.org/W2964029185","https://openalex.org/W3009083793","https://openalex.org/W3016180220","https://openalex.org/W3020986094","https://openalex.org/W3023686478","https://openalex.org/W3027934792","https://openalex.org/W3034889886","https://openalex.org/W3041337306","https://openalex.org/W3083085256","https://openalex.org/W3106393161","https://openalex.org/W3128159412","https://openalex.org/W3159843227","https://openalex.org/W3168163583","https://openalex.org/W3194530656","https://openalex.org/W3197013133","https://openalex.org/W3216563538","https://openalex.org/W4205708879","https://openalex.org/W4210480765","https://openalex.org/W4210532541","https://openalex.org/W4225512887","https://openalex.org/W4226208255","https://openalex.org/W4250657332","https://openalex.org/W4283837282","https://openalex.org/W4285113322","https://openalex.org/W4285504804","https://openalex.org/W4310638993","https://openalex.org/W4312322722","https://openalex.org/W4315629838","https://openalex.org/W4387449321"],"related_works":["https://openalex.org/W426968574","https://openalex.org/W2365639220","https://openalex.org/W2382520895","https://openalex.org/W2393709043","https://openalex.org/W2080567403","https://openalex.org/W2539387137","https://openalex.org/W2374952201","https://openalex.org/W2499112530","https://openalex.org/W2362413895","https://openalex.org/W4283655540"],"abstract_inverted_index":{"Radio":[0],"map":[1,26],"construction":[2,37],"requires":[3],"a":[4,16,23,41,50,108,113,141,155,179],"large":[5],"amount":[6],"of":[7,43],"radio":[8,25],"measurement":[9,47],"data":[10,48,78,95,147,209],"with":[11,82,112,150],"location":[12,34],"labels,":[13],"which":[14,131,206],"imposes":[15],"high":[17],"deployment":[18],"cost.":[19],"This":[20],"paper":[21],"develops":[22],"region-based":[24],"from":[27,49,162],"received":[28],"signal":[29,109],"strength":[30],"(RSS)":[31],"measurements":[32,161],"without":[33],"labels.":[35],"The":[36,70],"is":[38,73,116,129,132,148],"based":[39],"on":[40,159],"set":[42],"blindly":[44],"collected":[45],"RSS":[46,77,94,120],"device":[51],"that":[52],"visits":[53],"each":[54],"region":[55,171],"in":[56,140],"an":[57,123,163],"indoor":[58],"area":[59],"exactly":[60],"once,":[61],"where":[62],"the":[63,76,83,93,119,136,145,151,166,170],"footprints":[64],"and":[65,79,103,122,126,185,201],"timestamps":[66],"are":[67],"not":[68],"recorded.":[69],"main":[71],"challenge":[72],"to":[74,90,101,134,178],"cluster":[75],"match":[80],"clusters":[81],"physical":[84,152],"regions.":[85],"Classical":[86],"clustering":[87,127],"algorithms":[88],"fail":[89],"work":[91],"as":[92,98],"naturally":[96],"appears":[97],"non-clustered":[99],"due":[100],"multipaths":[102],"noise.":[104],"In":[105],"this":[106],"paper,":[107],"subspace":[110],"model":[111],"sequential":[114],"prior":[115],"constructed":[117],"for":[118,210],"data,":[121],"integrated":[124],"segmentation":[125],"algorithm":[128],"developed,":[130],"shown":[133],"find":[135],"globally":[137],"optimal":[138],"solution":[139],"special":[142],"case.":[143],"Furthermore,":[144],"clustered":[146],"matched":[149],"regions":[153],"using":[154],"graph-based":[156],"approach.":[157],"Based":[158],"real":[160],"office":[164],"space,":[165],"proposed":[167],"scheme":[168],"reduces":[169],"localization":[172,182,191],"error":[173],"by":[174],"roughly":[175],"50%":[176],"compared":[177],"weighted":[180],"centroid":[181],"(WCL)":[183],"baseline,":[184],"it":[186],"even":[187],"outperforms":[188],"some":[189],"supervised":[190],"schemes,":[192],"including":[193],"k-nearest":[194],"neighbor":[195],"(KNN),":[196],"support":[197],"vector":[198],"machine":[199],"(SVM),":[200],"deep":[202],"neural":[203],"network":[204],"(DNN),":[205],"require":[207],"labeled":[208],"training.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}