{"id":"https://openalex.org/W4306252958","doi":"https://doi.org/10.1145/3495243.3558280","title":"ST-ICM","display_name":"ST-ICM","publication_year":2022,"publication_date":"2022-10-14","ids":{"openalex":"https://openalex.org/W4306252958","doi":"https://doi.org/10.1145/3495243.3558280"},"language":"en","primary_location":{"id":"doi:10.1145/3495243.3558280","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3495243.3558280","pdf_url":null,"source":{"id":"https://openalex.org/S4363608994","display_name":"Proceedings of the 28th Annual International Conference on Mobile Computing And Networking","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th Annual International Conference on Mobile Computing And Networking","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/A5026742271","display_name":"Chengzhao Yu","orcid":"https://orcid.org/0000-0002-5283-5486"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengzhao Yu","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010264115","display_name":"Ji Luo","orcid":"https://orcid.org/0000-0003-1225-5310"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Luo","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031139851","display_name":"Rongye Shi","orcid":"https://orcid.org/0000-0003-4298-9358"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rongye Shi","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100446465","display_name":"Xinyu Liu","orcid":"https://orcid.org/0009-0009-1047-3139"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Liu","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011008509","display_name":"Fan Dang","orcid":"https://orcid.org/0000-0002-9949-6987"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Dang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016095713","display_name":"Xinlei Chen","orcid":"https://orcid.org/0000-0001-8271-5023"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinlei Chen","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9166,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86778198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"910","last_page":"912"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"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":0.9825000166893005,"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"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.7643461227416992},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7371784448623657},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5970546007156372},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5939189195632935},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4801158905029297},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4521489441394806},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4363860487937927},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4262353181838989},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4241373538970947},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3920256197452545},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33123424649238586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30642592906951904},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23537707328796387},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22950467467308044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1344502866268158}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7643461227416992},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7371784448623657},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5970546007156372},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5939189195632935},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4801158905029297},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4521489441394806},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4363860487937927},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4262353181838989},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4241373538970947},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3920256197452545},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33123424649238586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30642592906951904},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23537707328796387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22950467467308044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1344502866268158},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3495243.3558280","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3495243.3558280","pdf_url":null,"source":{"id":"https://openalex.org/S4363608994","display_name":"Proceedings of the 28th Annual International Conference on Mobile Computing And Networking","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th Annual International Conference on Mobile Computing And Networking","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":10,"referenced_works":["https://openalex.org/W149295781","https://openalex.org/W1503398984","https://openalex.org/W2547687744","https://openalex.org/W2548430090","https://openalex.org/W2763288875","https://openalex.org/W2791020134","https://openalex.org/W2791139480","https://openalex.org/W2899094839","https://openalex.org/W2944810452","https://openalex.org/W3002405259"],"related_works":["https://openalex.org/W2141609920","https://openalex.org/W4286748465","https://openalex.org/W4294619368","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W3118984993","https://openalex.org/W2144336328","https://openalex.org/W3196933554","https://openalex.org/W3041494753","https://openalex.org/W4380558509"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,86,95,131,153],"reduce":[3],"the":[4,12,25,31,50,66,68,97,100,105,110,115,133,136,154],"measurement":[5],"error":[6,150],"of":[7,27,33,89,104,135],"low":[8],"cost":[9],"sensor":[10],"in":[11,58,128],"real-time":[13],"mobile":[14],"sensing":[15],"network,":[16],"rendezvous":[17],"calibration":[18,34,51,56,151],"mechanism":[19],"is":[20],"widely":[21],"used.":[22],"To":[23],"tackle":[24],"sparsity":[26],"reference":[28],"data":[29],"and":[30,61,102],"lack":[32],"opportunities,":[35],"we":[36,84],"propose":[37,85],"ST-ICM:":[38],"a":[39,90,124],"Spatial-Temporal":[40],"Inference":[41],"Calibration":[42],"Model":[43],"based":[44],"on":[45,81,149],"Gaussian":[46],"Process":[47],"Regression,":[48],"assisting":[49],"task":[52],"by":[53,72],"creating":[54],"more":[55],"grids":[57,70,111],"both":[59],"spatial":[60],"temporal":[62],"dimensions.":[63],"By":[64],"using":[65,123],"GPR,":[67],"inferred":[69,106],"generated":[71],"ST-ICM":[73],"are":[74],"associated":[75],"with":[76,112],"various":[77],"confidence":[78],"levels.":[79],"Based":[80],"this":[82],"property,":[83],"make":[87],"use":[88],"hyperparameter,":[91],"i.e.,":[92],"variance":[93],"threshold,":[94],"balance":[96],"tradeoff":[98],"between":[99],"quantity":[101],"quality":[103],"grids.":[107],"Specifically,":[108],"only":[109],"variances":[113],"below":[114],"threshold":[116],"will":[117],"be":[118],"employed.":[119],"We":[120],"conducted":[121],"experiments":[122],"real-world":[125],"dataset":[126],"collected":[127],"Nanjing,":[129],"China,":[130],"evaluate":[132],"performance":[134],"proposed":[137],"ST-ICM.":[138],"The":[139],"experimenal":[140],"results":[141],"show":[142],"that":[143],"our":[144],"model":[145],"achieves":[146],"24%":[147],"improvement":[148],"compared":[152],"baseline.":[155]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2022-10-15T00:00:00"}
