{"id":"https://openalex.org/W2903831750","doi":"https://doi.org/10.1109/upinlbs.2018.8559873","title":"A shop-level location algorithm based on CNN for crowdsourcing fingerprint","display_name":"A shop-level location algorithm based on CNN for crowdsourcing fingerprint","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2903831750","doi":"https://doi.org/10.1109/upinlbs.2018.8559873","mag":"2903831750"},"language":"en","primary_location":{"id":"doi:10.1109/upinlbs.2018.8559873","is_oa":false,"landing_page_url":"https://doi.org/10.1109/upinlbs.2018.8559873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS)","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/A5030025128","display_name":"Xiao-Yun Zhou","orcid":"https://orcid.org/0000-0001-7886-8596"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoyun Zhou","raw_affiliation_strings":["School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004646219","display_name":"Jie Wei","orcid":"https://orcid.org/0009-0007-2496-4524"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wei","raw_affiliation_strings":["School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329778","display_name":"Fang Zhao","orcid":"https://orcid.org/0000-0002-4784-5778"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Zhao","raw_affiliation_strings":["School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052635380","display_name":"Haiyong Luo","orcid":"https://orcid.org/0000-0001-6827-4225"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyong Luo","raw_affiliation_strings":["Insititude of Computing Technology Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Insititude of Computing Technology Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023621528","display_name":"Langlang Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Langlang Ye","raw_affiliation_strings":["Insititude of Computing Technology Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Insititude of Computing Technology Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030025128"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13561887,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9943000078201294,"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"}},{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.988099992275238,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7625831365585327},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.6002268195152283},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.5136329531669617},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.506482720375061},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4895537793636322},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46191099286079407},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.431369423866272},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42923614382743835},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4233127534389496},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.3305121660232544}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7625831365585327},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.6002268195152283},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.5136329531669617},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.506482720375061},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4895537793636322},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46191099286079407},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.431369423866272},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42923614382743835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4233127534389496},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.3305121660232544},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/upinlbs.2018.8559873","is_oa":false,"landing_page_url":"https://doi.org/10.1109/upinlbs.2018.8559873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W204612701","https://openalex.org/W1588137027","https://openalex.org/W1954066267","https://openalex.org/W1979154650","https://openalex.org/W2005598601","https://openalex.org/W2095705004","https://openalex.org/W2100989187","https://openalex.org/W2163993204","https://openalex.org/W2336558231","https://openalex.org/W2343107556","https://openalex.org/W2475334473","https://openalex.org/W2524455649","https://openalex.org/W2552748925","https://openalex.org/W2566081151","https://openalex.org/W2741050456","https://openalex.org/W2770877176","https://openalex.org/W2790384971","https://openalex.org/W2919115771","https://openalex.org/W2949117887","https://openalex.org/W2999214452","https://openalex.org/W4251708881","https://openalex.org/W6608207920"],"related_works":["https://openalex.org/W3014822659","https://openalex.org/W2117826006","https://openalex.org/W4362496757","https://openalex.org/W2051501574","https://openalex.org/W2124627279","https://openalex.org/W2050967184","https://openalex.org/W2566091814","https://openalex.org/W2114937328","https://openalex.org/W2148654711","https://openalex.org/W2608025327"],"abstract_inverted_index":{"Recent":[0],"years,":[1],"the":[2,25,50,59,63,66,73,82,90,121,128,136,143,151,156,163,174,191,205,219,231],"use":[3],"of":[4,40,52,92,117,130,142,158,166,178,187,208,213],"widely":[5],"covered":[6],"Wi-Fi":[7,20,53,77,179],"signal":[8,107],"to":[9,48,97,132,147,197,203],"achieve":[10],"accurate":[11,84],"indoor":[12],"positioning":[13,32,85,201,225,232],"has":[14],"become":[15],"a":[16,37,102,199],"research":[17],"hotspot.":[18],"The":[19,115,139],"Positioning":[21],"Algorithm":[22],"based":[23,234],"on":[24,89,235],"existing":[26],"RF":[27,78],"Fingerprint":[28],"can":[29,222],"obtain":[30,223],"high":[31],"accuracy,":[33],"but":[34],"there":[35],"is":[36,146,172],"big":[38],"shortage":[39],"large":[41,211],"deployment":[42],"and":[43,80,112,169,180,239],"maintenance":[44],"cost.":[45],"In":[46,160],"order":[47],"reduce":[49],"cost":[51,75],"fingerprints":[54],"collection,":[55],"this":[56,99,161],"paper":[57,100],"utilizes":[58],"RSS":[60],"collected":[61],"by":[62,126,155,227],"consumers":[64],"using":[65,127],"mobile":[67],"phone":[68],"for":[69],"electronic":[70],"payment,":[71],"constructs":[72,101],"low":[74],"crowdsourcing":[76],"Fingerprint,":[79],"realizes":[81],"shop-level":[83],"with":[86,230],"CNN.":[87],"Based":[88],"feature":[91,119,164,171,176],"CNN":[93,200],"extraction":[94],"from":[95],"local":[96],"global,":[98],"characteristic":[103],"group":[104],"which":[105],"includes":[106],"intensity,":[108],"user":[109],"transaction":[110],"time":[111],"shop":[113],"information.":[114],"statistics":[116],"each":[118],"in":[120,150],"statistical":[122,144],"interval":[123,129],"are":[124,182,195],"obtained":[125],"1":[131],"23":[133],"days":[134],"before":[135],"current":[137],"time.":[138],"Min-Max":[140],"normalization":[141],"value":[145],"avoid":[148],"inconsistencies":[149],"data":[152,215],"distribution":[153],"caused":[154],"loss":[157],"data.":[159],"way,":[162],"map":[165],"window":[167],"length":[168],"statistic":[170],"constructed,":[173],"different":[175],"groups":[177],"Shop":[181],"used":[183],"as":[184],"input":[185],"matrices":[186],"multiple":[188],"CNN,":[189],"then":[190],"other":[192],"manual":[193],"features":[194],"combined":[196],"train":[198],"classifier":[202],"realize":[204],"position":[206],"estimation":[207],"shop-level.":[209],"A":[210],"number":[212],"experimental":[214],"tests":[216],"show":[217],"that":[218],"proposed":[220],"algorithm":[221,233],"higher":[224],"accuracy":[226],"91%":[228],"compared":[229],"LR(Logistic":[236],"Regression),":[237],"AdaBoost":[238],"XGBoost.":[240]},"counts_by_year":[],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
