{"id":"https://openalex.org/W2010010818","doi":"https://doi.org/10.1109/wimob.2013.6673417","title":"REPSense: On-line sensor data reduction while preserving data diversity for mobile sensing","display_name":"REPSense: On-line sensor data reduction while preserving data diversity for mobile sensing","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W2010010818","doi":"https://doi.org/10.1109/wimob.2013.6673417","mag":"2010010818"},"language":"en","primary_location":{"id":"doi:10.1109/wimob.2013.6673417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wimob.2013.6673417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)","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/A5009649482","display_name":"Guangwen Liu","orcid":"https://orcid.org/0000-0002-2521-0894"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Guangwen Liu","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo","Inst. of Ind. Sci., Univ. of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Inst. of Ind. Sci., Univ. of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025094439","display_name":"Masayuki Iwai","orcid":null},"institutions":[{"id":"https://openalex.org/I165522056","display_name":"Tokyo Denki University","ror":"https://ror.org/01pa62v70","country_code":"JP","type":"education","lineage":["https://openalex.org/I165522056"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masayuki Iwai","raw_affiliation_strings":["Tokyo Denki University, Japan","TOKYO DENKI Univ., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Denki University, Japan","institution_ids":["https://openalex.org/I165522056"]},{"raw_affiliation_string":"TOKYO DENKI Univ., Tokyo, Japan","institution_ids":["https://openalex.org/I165522056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004589876","display_name":"Yoshito Tobe","orcid":"https://orcid.org/0000-0002-1795-5829"},"institutions":[{"id":"https://openalex.org/I131231118","display_name":"Aoyama Gakuin University","ror":"https://ror.org/002rw7y37","country_code":"JP","type":"education","lineage":["https://openalex.org/I131231118"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshito Tobe","raw_affiliation_strings":["Aoyama Gakuin University, Japan","Aoyama Gakuin University, Sagamihara, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aoyama Gakuin University, Japan","institution_ids":["https://openalex.org/I131231118"]},{"raw_affiliation_string":"Aoyama Gakuin University, Sagamihara, Japan","institution_ids":["https://openalex.org/I131231118"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050720322","display_name":"Kaoru Sezaki","orcid":"https://orcid.org/0000-0003-1194-4632"},"institutions":[{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]},{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kaoru Sezaki","raw_affiliation_strings":["Center for Spatial Information Science, The University of Tokyo","Center for Spatial Information Science, University of Tokyo, Tokyo, Japan,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Spatial Information Science, The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Center for Spatial Information Science, University of Tokyo, Tokyo, Japan,","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I161296585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"584","last_page":"591"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9984999895095825,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7745199203491211},{"id":"https://openalex.org/keywords/delegate","display_name":"Delegate","score":0.7019381523132324},{"id":"https://openalex.org/keywords/participatory-sensing","display_name":"Participatory sensing","score":0.4995748996734619},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.49656420946121216},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.484510600566864},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4707126021385193},{"id":"https://openalex.org/keywords/data-reduction","display_name":"Data reduction","score":0.4421241283416748},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43747496604919434},{"id":"https://openalex.org/keywords/data-processing","display_name":"Data processing","score":0.4175875782966614},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4162946343421936},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.20436948537826538},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1134103536605835}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7745199203491211},{"id":"https://openalex.org/C143273055","wikidata":"https://www.wikidata.org/wiki/Q2382794","display_name":"Delegate","level":2,"score":0.7019381523132324},{"id":"https://openalex.org/C2779208394","wikidata":"https://www.wikidata.org/wiki/Q7140460","display_name":"Participatory sensing","level":2,"score":0.4995748996734619},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.49656420946121216},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.484510600566864},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4707126021385193},{"id":"https://openalex.org/C153914771","wikidata":"https://www.wikidata.org/wiki/Q5227343","display_name":"Data reduction","level":2,"score":0.4421241283416748},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43747496604919434},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.4175875782966614},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4162946343421936},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.20436948537826538},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1134103536605835},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wimob.2013.6673417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wimob.2013.6673417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W202801672","https://openalex.org/W1553085258","https://openalex.org/W1578468649","https://openalex.org/W2005622485","https://openalex.org/W2027130402","https://openalex.org/W2038134612","https://openalex.org/W2038323322","https://openalex.org/W2043455251","https://openalex.org/W2047519109","https://openalex.org/W2073004415","https://openalex.org/W2077451659","https://openalex.org/W2091283109","https://openalex.org/W2104266187","https://openalex.org/W2112824976","https://openalex.org/W2136317921","https://openalex.org/W2143371192","https://openalex.org/W2144193487","https://openalex.org/W2148694408","https://openalex.org/W2150882603","https://openalex.org/W2168720188","https://openalex.org/W2295549646","https://openalex.org/W3141232563","https://openalex.org/W4292023222"],"related_works":["https://openalex.org/W2031284701","https://openalex.org/W3141203889","https://openalex.org/W1969486489","https://openalex.org/W2156039046","https://openalex.org/W2418771911","https://openalex.org/W2994187804","https://openalex.org/W2960441665","https://openalex.org/W2070558560","https://openalex.org/W134453586","https://openalex.org/W3030452487"],"abstract_inverted_index":{"Pervasive":[0],"smartphones":[1],"that":[2,137],"embed":[3],"a":[4,56,129],"variety":[5],"of":[6,30,41,62,70,131,148],"sensors":[7],"enable":[8],"us":[9],"to":[10,58,104],"sense":[11],"and":[12,48,151],"learn":[13],"about":[14],"the":[15,21,27,39,60,67,71,81,95],"physical":[16],"environment":[17],"around":[18],"us,":[19],"even":[20],"society":[22],"we":[23,54],"live":[24],"in.":[25],"However,":[26],"sheer":[28],"volume":[29,61],"data":[31,45,64,88,91,97,113,149,152],"collected":[32,124],"through":[33],"participatory":[34],"sensing":[35],"can":[36,93,110],"deeply":[37],"hamper":[38],"performance":[40],"various":[42],"applications":[43],"(e.g.,":[44],"processing":[46,153],"time":[47],"transmitting":[49],"cost).":[50],"In":[51],"this":[52],"paper,":[53],"proposed":[55,75],"method":[57,76,109,120,139],"reduce":[59],"sensor":[63],"while":[65],"preserving":[66],"information":[68],"content":[69],"original":[72,96],"data.":[73],"Our":[74],"REPresentative":[77],"Sense":[78],"(REPSense)":[79],"borrows":[80],"idea":[82],"from":[83],"electoral":[84],"system.":[85],"Hence,":[86],"after":[87],"reduction,":[89],"output":[90],"(target)":[92],"represent":[94],"(source)":[98],"as":[99],"parliament":[100],"members":[101],"are":[102],"elected":[103],"delegate":[105],"their":[106],"constituencies.":[107],"This":[108],"compress":[111],"multi-dimensional":[112],"with":[114],"arbitrary":[115],"distribution.":[116],"We":[117],"evaluated":[118],"our":[119,138],"using":[121],"real-world":[122],"datasets":[123],"by":[125,142],"12":[126],"users":[127],"over":[128],"period":[130],"4":[132],"months.":[133],"The":[134],"results":[135],"show":[136],"outperforms":[140],"state-of-the-art":[141],"comparing":[143],"baseline":[144],"methods":[145],"in":[146],"terms":[147],"divergence":[150],"performance.":[154]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
