{"id":"https://openalex.org/W2165178985","doi":"https://doi.org/10.1145/2632048.2632102","title":"Diagnosing New York city's noises with ubiquitous data","display_name":"Diagnosing New York city's noises with ubiquitous data","publication_year":2014,"publication_date":"2014-09-13","ids":{"openalex":"https://openalex.org/W2165178985","doi":"https://doi.org/10.1145/2632048.2632102","mag":"2165178985"},"language":"en","primary_location":{"id":"doi:10.1145/2632048.2632102","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2632048.2632102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing","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/A5100681023","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0002-5224-4344"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392623","display_name":"Tong Liu","orcid":"https://orcid.org/0000-0001-8678-6291"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Liu","raw_affiliation_strings":["Microsoft Research, Beijing, China and Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China and Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694459","display_name":"Yilun Wang","orcid":"https://orcid.org/0000-0002-7324-6007"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilun Wang","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081759167","display_name":"Yanmin Zhu","orcid":"https://orcid.org/0000-0001-6406-4992"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanmin Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101594832","display_name":"Yanchi Liu","orcid":"https://orcid.org/0000-0003-4396-5139"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanchi Liu","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087298985","display_name":"Eric Chang","orcid":"https://orcid.org/0000-0002-9678-5994"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Eric Chang","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":42.4103,"has_fulltext":false,"cited_by_count":226,"citation_normalized_percentile":{"value":0.99879032,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"715","last_page":"725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9973999857902527,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9973999857902527,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12303","display_name":"Tensor decomposition and applications","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7438310980796814},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6411193609237671},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.621406078338623},{"id":"https://openalex.org/keywords/complaint","display_name":"Complaint","score":0.6106226444244385},{"id":"https://openalex.org/keywords/noise-pollution","display_name":"Noise pollution","score":0.5492891073226929},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.514279305934906},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.478985071182251},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.47756797075271606},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4720514714717865},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.46132129430770874},{"id":"https://openalex.org/keywords/phone","display_name":"Phone","score":0.4418559968471527},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.37848109006881714},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3568700850009918},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3165799081325531},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.30935555696487427},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.28333964943885803},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.21581971645355225},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.19249460101127625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11602562665939331}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7438310980796814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6411193609237671},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.621406078338623},{"id":"https://openalex.org/C2780838233","wikidata":"https://www.wikidata.org/wiki/Q836925","display_name":"Complaint","level":2,"score":0.6106226444244385},{"id":"https://openalex.org/C130858481","wikidata":"https://www.wikidata.org/wiki/Q92251","display_name":"Noise pollution","level":3,"score":0.5492891073226929},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.514279305934906},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.478985071182251},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.47756797075271606},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4720514714717865},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.46132129430770874},{"id":"https://openalex.org/C2778707766","wikidata":"https://www.wikidata.org/wiki/Q202064","display_name":"Phone","level":2,"score":0.4418559968471527},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.37848109006881714},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3568700850009918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3165799081325531},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.30935555696487427},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28333964943885803},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.21581971645355225},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19249460101127625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11602562665939331},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","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},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2632048.2632102","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2632048.2632102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing","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":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W98895690","https://openalex.org/W186390037","https://openalex.org/W1561603276","https://openalex.org/W1583075929","https://openalex.org/W1986149296","https://openalex.org/W1997527178","https://openalex.org/W1998812539","https://openalex.org/W2024165284","https://openalex.org/W2032360374","https://openalex.org/W2044035162","https://openalex.org/W2056079853","https://openalex.org/W2102937240","https://openalex.org/W2106403424","https://openalex.org/W2108950108","https://openalex.org/W2112738128","https://openalex.org/W2115536324","https://openalex.org/W2116272996","https://openalex.org/W2117587045","https://openalex.org/W2122516730","https://openalex.org/W2126281861","https://openalex.org/W2127347346","https://openalex.org/W2137100320","https://openalex.org/W2144475703","https://openalex.org/W2149128936","https://openalex.org/W2153207204","https://openalex.org/W2155211535","https://openalex.org/W2158608926","https://openalex.org/W2171679232","https://openalex.org/W2462818938","https://openalex.org/W3100612189","https://openalex.org/W6604031572"],"related_works":["https://openalex.org/W4379256054","https://openalex.org/W2093953080","https://openalex.org/W47805180","https://openalex.org/W2963838862","https://openalex.org/W3015641590","https://openalex.org/W3216281372","https://openalex.org/W2987657992","https://openalex.org/W2949531434","https://openalex.org/W3155683369","https://openalex.org/W4286927328"],"abstract_inverted_index":{"Many":[0],"cities":[1],"suffer":[2],"from":[3],"noise":[4,44,72,111,116,155,171,193],"pollution,":[5],"which":[6],"compromises":[7],"people's":[8],"working":[9],"efficiency":[10],"and":[11,69,91,119,147,173,202],"even":[12],"mental":[13],"health.":[14],"New":[15],"York":[16],"City":[17],"(NYC)":[18],"has":[19],"opened":[20],"a":[21,36,41,64,66,70,84,89,115,160,185],"platform,":[22],"entitled":[23],"311,":[24],"to":[25,28],"allow":[26],"people":[27,201],"complain":[29],"about":[30,59],"the":[31,46,53,80,109,120,136,154,165,178,182,192,215,225],"city's":[32],"issues":[33],"by":[34,134],"using":[35,135],"mobile":[37],"app":[38],"or":[39,78],"making":[40],"phone":[42],"call;":[43],"is":[45,61,82],"third":[47],"largest":[48],"category":[49],"of":[50,86,114,122,124,127,132,149,157,181,217],"complaints":[51],"in":[52],"311":[54,137],"data.":[55],"As":[56],"each":[57,130],"complaint":[58,138],"noises":[60],"associated":[62],"with":[63,141,159,210],"location,":[65],"time":[67,174],"stamp,":[68],"fine-grained":[71,110],"category,":[73],"such":[74,223],"as":[75,88,224],"\"Loud":[76],"Music\"":[77],"\"Construction\",":[79],"data":[81,139],"actually":[83],"result":[85],"\"human":[87],"sensor\"":[90],"\"crowd":[92],"sensing\",":[93],"containing":[94],"rich":[95],"human":[96],"intelligence":[97],"that":[98],"can":[99,199],"help":[100],"diagnose":[101],"urban":[102],"noises.":[103],"In":[104],"this":[105],"paper":[106],"we":[107,190],"infer":[108],"situation":[112,156,194],"(consisting":[113],"pollution":[117],"indicator":[118],"composition":[121],"noises)":[123],"different":[125],"times":[126],"day":[128],"for":[129,169],"region":[131],"NYC,":[133],"together":[140],"social":[142],"media,":[143],"road":[144],"network":[145],"data,":[146],"Points":[148],"Interests":[150],"(POIs).":[151],"We":[152,206],"model":[153],"NYC":[158],"three":[161,166],"dimension":[162],"tensor,":[163],"where":[164],"dimensions":[167],"stand":[168],"regions,":[170],"categories,":[172],"slots,":[175],"respectively.":[176],"Supplementing":[177],"missing":[179],"entries":[180],"tensor":[183,187],"through":[184],"context-aware":[186],"decomposition":[188],"approach,":[189],"recover":[191],"throughout":[195],"NYC.":[196],"The":[197],"information":[198],"inform":[200],"officials'":[203],"decision":[204],"making.":[205],"evaluate":[207],"our":[208,218],"method":[209,219],"four":[211,221],"real":[212],"datasets,":[213],"verifying":[214],"advantages":[216],"beyond":[220],"baselines,":[222],"interpolation-based":[226],"approach.":[227]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":32},{"year":2019,"cited_by_count":22},{"year":2018,"cited_by_count":36},{"year":2017,"cited_by_count":30},{"year":2016,"cited_by_count":34},{"year":2015,"cited_by_count":18},{"year":2014,"cited_by_count":6}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
