{"id":"https://openalex.org/W2537619628","doi":"https://doi.org/10.1145/2983323.2983902","title":"Forecasting Geo-sensor Data with Participatory Sensing Based on Dropout Neural Network","display_name":"Forecasting Geo-sensor Data with Participatory Sensing Based on Dropout Neural Network","publication_year":2016,"publication_date":"2016-10-24","ids":{"openalex":"https://openalex.org/W2537619628","doi":"https://doi.org/10.1145/2983323.2983902","mag":"2537619628"},"language":"en","primary_location":{"id":"doi:10.1145/2983323.2983902","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2983323.2983902","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM International on Conference on Information and Knowledge Management","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/A5048749901","display_name":"Jyun\u2010Yu Jiang","orcid":"https://orcid.org/0000-0002-1753-8099"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jyun-Yu Jiang","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014600496","display_name":"Cheng\u2013Te Li","orcid":"https://orcid.org/0000-0001-7995-4787"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Te Li","raw_affiliation_strings":["National Cheng Kung University, Tainan, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Cheng Kung University, Tainan, Taiwan Roc","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048749901"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.08985417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2033","last_page":"2036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9776999950408936,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9767000079154968,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/participatory-sensing","display_name":"Participatory sensing","score":0.8282131552696228},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7010085582733154},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.6448517441749573},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5556076169013977},{"id":"https://openalex.org/keywords/air-quality-index","display_name":"Air quality index","score":0.47837796807289124},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4682045578956604},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.429245263338089},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4282499849796295},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.41483911871910095},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3863186240196228},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3435731530189514},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.21585199236869812},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14816221594810486},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09230184555053711},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08294081687927246},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.08027386665344238}],"concepts":[{"id":"https://openalex.org/C2779208394","wikidata":"https://www.wikidata.org/wiki/Q7140460","display_name":"Participatory sensing","level":2,"score":0.8282131552696228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7010085582733154},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.6448517441749573},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5556076169013977},{"id":"https://openalex.org/C126314574","wikidata":"https://www.wikidata.org/wiki/Q2364111","display_name":"Air quality index","level":2,"score":0.47837796807289124},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4682045578956604},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.429245263338089},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4282499849796295},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.41483911871910095},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3863186240196228},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3435731530189514},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.21585199236869812},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14816221594810486},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09230184555053711},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08294081687927246},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.08027386665344238},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2983323.2983902","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2983323.2983902","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W140193802","https://openalex.org/W1775899153","https://openalex.org/W1969865391","https://openalex.org/W1971402834","https://openalex.org/W2003831290","https://openalex.org/W2016210396","https://openalex.org/W2032576386","https://openalex.org/W2095705004","https://openalex.org/W2112738128","https://openalex.org/W2157539394","https://openalex.org/W2297059404"],"related_works":["https://openalex.org/W3082178636","https://openalex.org/W1970299606","https://openalex.org/W2063769785","https://openalex.org/W1521968289","https://openalex.org/W2782041652","https://openalex.org/W2952088488","https://openalex.org/W2612657834","https://openalex.org/W2392157706","https://openalex.org/W2599192953","https://openalex.org/W2268621700"],"abstract_inverted_index":{"Nowadays,":[0],"geosensor":[1,86,138,192],"data,":[2],"such":[3],"as":[4,191],"air":[5,158,184],"quality":[6,159,185],"and":[7,13,29,107,113,163,186],"traffic":[8,165,190],"flow,":[9],"have":[10,38,150],"become":[11],"more":[12,14],"essential":[15],"in":[16,123,140,160,170],"people's":[17],"daily":[18],"life.":[19],"However,":[20],"installing":[21],"geosensors":[22],"or":[23,42,97],"hiring":[24],"volunteers":[25],"at":[26,110,114],"every":[27,30],"location":[28,142],"time":[31],"is":[32],"so":[33],"expensive.":[34],"Some":[35],"organizations":[36],"may":[37],"only":[39],"few":[40],"facilities":[41],"limited":[43,93],"budget":[44],"to":[45,53,72,84,134],"sense":[46],"these":[47,119],"data.":[48,193],"Moreover,":[49],"people":[50],"usually":[51],"tend":[52],"know":[54],"the":[55,62,124,136,157,164,183,187],"forecast":[56,85,135,182],"instead":[57],"of":[58,64,95,103,143,156,166],"ongoing":[59],"observations,":[60],"but":[61],"number":[63,94],"sensors":[65,96],"(or":[66],"volunteers)":[67],"will":[68],"be":[69],"a":[70,81,92,129],"hurdle":[71],"make":[73],"precise":[74],"prediction.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79,127],"propose":[80,128],"novel":[82],"concept":[83],"data":[87,109,121,139],"with":[88,153],"participatory":[89,99],"sensing.":[90],"Given":[91],"volunteers,":[98],"sensing":[100],"assumes":[101],"each":[102],"them":[104],"can":[105,180],"observe":[106],"collect":[108],"different":[111,115],"locations":[112],"time.":[116],"By":[117],"aggregating":[118],"sparse":[120],"observations":[122],"past":[125],"time,":[126],"neural":[130],"network":[131],"based":[132],"approach":[133],"future":[137],"any":[141],"an":[144],"urban":[145],"area.":[146],"The":[147],"extensive":[148],"experiments":[149],"been":[151],"conducted":[152],"large-scale":[154],"datasets":[155],"three":[161],"cities":[162],"bike":[167,188],"sharing":[168],"systems":[169],"two":[171],"cities.":[172],"Experimental":[173],"results":[174],"show":[175],"that":[176],"our":[177],"predictive":[178],"model":[179],"precisely":[181],"rentle":[189]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}