{"id":"https://openalex.org/W3092020416","doi":"https://doi.org/10.1109/tits.2020.3025948","title":"STAP: A Spatio-Temporal Correlative Estimating Model for Improving Quality of Traffic Data","display_name":"STAP: A Spatio-Temporal Correlative Estimating Model for Improving Quality of Traffic Data","publication_year":2020,"publication_date":"2020-10-06","ids":{"openalex":"https://openalex.org/W3092020416","doi":"https://doi.org/10.1109/tits.2020.3025948","mag":"3092020416"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2020.3025948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.3025948","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5044918612","display_name":"Yingjie Xia","orcid":"https://orcid.org/0000-0002-4642-2503"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Xia","raw_affiliation_strings":["College of Computer Sciences, Zhejiang University, Hangzhou, China","Hangzhou Yuantiao Technology Company, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4642-2503","affiliations":[{"raw_affiliation_string":"College of Computer Sciences, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Hangzhou Yuantiao Technology Company, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403440","display_name":"Fan Zhang","orcid":"https://orcid.org/0000-0002-1792-5195"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Zhang","raw_affiliation_strings":["College of Computer Sciences, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Sciences, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075706294","display_name":"Jing Ou","orcid":"https://orcid.org/0000-0001-8097-2747"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Ou","raw_affiliation_strings":["College of Computer Sciences, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Sciences, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.1268,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.49383434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"23","issue":"3","first_page":"1746","last_page":"1754"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9997000098228455,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9958999752998352,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/correlative","display_name":"Correlative","score":0.7542617321014404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6668915748596191},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6318106055259705},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5372331738471985},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.5060307383537292},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.49460670351982117},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.481106698513031},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.43928617238998413},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.425041139125824},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.42007213830947876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3611202836036682},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13539686799049377},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.07724636793136597}],"concepts":[{"id":"https://openalex.org/C2776800370","wikidata":"https://www.wikidata.org/wiki/Q5172864","display_name":"Correlative","level":2,"score":0.7542617321014404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6668915748596191},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6318106055259705},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5372331738471985},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.5060307383537292},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.49460670351982117},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.481106698513031},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.43928617238998413},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.425041139125824},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42007213830947876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3611202836036682},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13539686799049377},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.07724636793136597},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2020.3025948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.3025948","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6700000166893005,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G438397208","display_name":null,"funder_award_id":"61873232","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W656701260","https://openalex.org/W1525147170","https://openalex.org/W1548161163","https://openalex.org/W1554683730","https://openalex.org/W1577395830","https://openalex.org/W1973737652","https://openalex.org/W1980453015","https://openalex.org/W1991770012","https://openalex.org/W1999432478","https://openalex.org/W2004686034","https://openalex.org/W2004891103","https://openalex.org/W2027392238","https://openalex.org/W2038436579","https://openalex.org/W2080180737","https://openalex.org/W2086482048","https://openalex.org/W2088400370","https://openalex.org/W2117618130","https://openalex.org/W2137393925","https://openalex.org/W2145039203","https://openalex.org/W2145527836","https://openalex.org/W2203482404","https://openalex.org/W2307933510","https://openalex.org/W2399880423","https://openalex.org/W2463516922","https://openalex.org/W2463827188","https://openalex.org/W2530386080","https://openalex.org/W2565115916","https://openalex.org/W2572939427","https://openalex.org/W2579495707","https://openalex.org/W2580695889","https://openalex.org/W2593576175","https://openalex.org/W2613331518","https://openalex.org/W2615783694","https://openalex.org/W2743812350","https://openalex.org/W2751760169","https://openalex.org/W2758028572","https://openalex.org/W2760337674","https://openalex.org/W2808673810","https://openalex.org/W2884128153","https://openalex.org/W2902838572","https://openalex.org/W2909550475","https://openalex.org/W2909745252","https://openalex.org/W2963536745","https://openalex.org/W3106224380","https://openalex.org/W6633414439","https://openalex.org/W6676105031","https://openalex.org/W6738698023"],"related_works":["https://openalex.org/W2899273011","https://openalex.org/W2547829566","https://openalex.org/W3081133439","https://openalex.org/W2050347474","https://openalex.org/W2541259009","https://openalex.org/W638142098","https://openalex.org/W1975124777","https://openalex.org/W4386246791","https://openalex.org/W2019425806","https://openalex.org/W3211701140"],"abstract_inverted_index":{"With":[0],"the":[1,28,34,98,125,129],"rapid":[2],"development":[3],"of":[4,30],"intelligent":[5],"transportation":[6],"systems":[7],"(ITS),":[8],"traffic":[9,20,37,50,115],"data":[10,21,38,103,116,136],"plays":[11],"a":[12,24,45,66,119],"more":[13,15],"and":[14,55,85,90,93,124],"important":[16],"role.":[17],"Low":[18],"quality":[19,46],"has":[22],"become":[23],"challenging":[25],"issue":[26],"in":[27,134],"implementation":[29],"ITS.":[31],"Inspired":[32],"by":[33],"fact":[35],"that":[36,128],"have":[39],"strong":[40],"spatio-temporal":[41,67],"correlation,":[42],"we":[43],"propose":[44],"improving":[47,135],"model":[48,70,99,131],"for":[49],"data,":[51],"which":[52,71],"correlates":[53],"spatial":[54,92],"temporal":[56,94],"features":[57,89,95],"to":[58,106],"fix":[59,107],"abnormal":[60,108],"data.":[61,109],"We":[62,110],"call":[63],"it":[64],"STAP,":[65],"correlative":[68],"estimating":[69],"firstly":[72],"proposes":[73,100],"an":[74,80,101],"anomalies":[75],"detection":[76],"algorithm":[77,105],"based":[78],"on":[79,113],"improved":[81],"Random":[82],"Forest":[83],"model,":[84],"then":[86],"classifies":[87],"traditional":[88],"extracts":[91],"respectively.":[96],"Finally":[97],"XGboost-based":[102],"estimation":[104],"conduct":[111],"experiments":[112],"real":[114],"collected":[117],"from":[118],"big":[120],"China":[121],"city,":[122],"Changsha,":[123],"results":[126],"show":[127],"STAP":[130],"is":[132],"effective":[133],"quality.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
