{"id":"https://openalex.org/W2387506654","doi":"https://doi.org/10.1145/2939672.2939799","title":"Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks","display_name":"Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks","publication_year":2016,"publication_date":"2016-08-08","ids":{"openalex":"https://openalex.org/W2387506654","doi":"https://doi.org/10.1145/2939672.2939799","mag":"2387506654"},"language":"en","primary_location":{"id":"doi:10.1145/2939672.2939799","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","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/A5101570536","display_name":"Tong Xu","orcid":"https://orcid.org/0000-0001-5564-192X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Xu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049015446","display_name":"Hengshu Zhu","orcid":"https://orcid.org/0000-0003-4570-643X"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengshu Zhu","raw_affiliation_strings":["Baidu Research-Big Data Lab, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research-Big Data Lab, Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100645851","display_name":"Xiangyu Zhao","orcid":"https://orcid.org/0000-0002-7721-6227"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyu Zhao","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100453144","display_name":"Qi Liu","orcid":"https://orcid.org/0000-0001-5378-6404"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Liu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101419246","display_name":"Hao Zhong","orcid":"https://orcid.org/0000-0001-5947-1729"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Zhong","raw_affiliation_strings":["Rutgers, the State University of New Jersey, Newark, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey, Newark, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048237545","display_name":"Enhong Chen","orcid":"https://orcid.org/0000-0002-4835-4102"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhong Chen","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101862104","display_name":"Hui Xiong","orcid":"https://orcid.org/0000-0001-6016-6465"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Xiong","raw_affiliation_strings":["Rutgers, the State University of New Jersey, Newark, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey, Newark, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.8078,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.98769031,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1285","last_page":"1294"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/predictability","display_name":"Predictability","score":0.7407163381576538},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6591583490371704},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4347924292087555},{"id":"https://openalex.org/keywords/profit","display_name":"Profit (economics)","score":0.42526257038116455}],"concepts":[{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.7407163381576538},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6591583490371704},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4347924292087555},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.42526257038116455},{"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2939672.2939799","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W26726511","https://openalex.org/W61631330","https://openalex.org/W107622521","https://openalex.org/W118616697","https://openalex.org/W1856548066","https://openalex.org/W1937847179","https://openalex.org/W1953266353","https://openalex.org/W1976993400","https://openalex.org/W1982300822","https://openalex.org/W1982610444","https://openalex.org/W2018936209","https://openalex.org/W2025766355","https://openalex.org/W2027135291","https://openalex.org/W2031674781","https://openalex.org/W2042123098","https://openalex.org/W2061820396","https://openalex.org/W2073926352","https://openalex.org/W2075364600","https://openalex.org/W2077933964","https://openalex.org/W2097241863","https://openalex.org/W2101108259","https://openalex.org/W2101823987","https://openalex.org/W2106111489","https://openalex.org/W2109341352","https://openalex.org/W2110953678","https://openalex.org/W2127526138","https://openalex.org/W2136975357","https://openalex.org/W2138198492","https://openalex.org/W2140540364","https://openalex.org/W2147318892","https://openalex.org/W2152204876","https://openalex.org/W2161581167","https://openalex.org/W2166692930","https://openalex.org/W2168884627","https://openalex.org/W2168903146","https://openalex.org/W2221382652","https://openalex.org/W2394587288","https://openalex.org/W2401884355","https://openalex.org/W2947626232"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2726467123","https://openalex.org/W2064726690","https://openalex.org/W4252678288","https://openalex.org/W4254065731","https://openalex.org/W1607297154","https://openalex.org/W4210820789","https://openalex.org/W4237782192","https://openalex.org/W2913177154"],"abstract_inverted_index":{"With":[0],"recent":[1],"advances":[2],"in":[3,64,102],"mobile":[4],"and":[5,27,33,48,98],"sensor":[6],"technologies,":[7],"a":[8,69,127,144],"large":[9],"amount":[10],"of":[11,82,112,158,180],"efforts":[12],"have":[13],"been":[14,58],"made":[15],"on":[16,40,143,162],"developing":[17],"intelligent":[18],"applications":[19],"for":[20,79,130],"taxi":[21,139,165],"drivers,":[22,47],"which":[23,107,168],"provide":[24],"beneficial":[25],"guide":[26],"opportunity":[28],"to":[29,53,72],"improve":[30,177],"the":[31,41,75,93,103,110,120,133,150,156,171,178],"profit":[32],"work":[34],"efficiency.":[35],"However,":[36],"limited":[37],"scopes":[38],"focus":[39],"latent":[42,104,134],"social":[43,50,76,113,122,174],"interaction":[44],"within":[45,138],"cab":[46,83],"corresponding":[49],"propagation":[51,77,137],"scheme":[52],"share":[54],"driving":[55,135,166,181],"behaviors":[56],"has":[57],"largely":[59],"ignored.":[60],"To":[61,87],"that":[62,173],"end,":[63],"this":[65,116],"paper,":[66],"we":[67,90,125],"propose":[68],"comprehensive":[70],"study":[71],"reveal":[73],"how":[74],"affects":[78],"better":[80],"prediction":[81],"drivers'":[84,96],"future":[85,164],"behaviors.":[86,182],"be":[88],"specific,":[89],"first":[91],"investigate":[92],"correlation":[94],"between":[95],"skills":[97],"their":[99],"mutual":[100],"interactions":[101],"vehicle-to-vehicle":[105],"network,":[106],"intuitively":[108],"indicates":[109],"effects":[111],"influences.":[114],"Along":[115],"line,":[117],"by":[118],"leveraging":[119],"classic":[121],"influence":[123],"theory,":[124],"develop":[126],"two-stage":[128],"framework":[129,161],"quantitatively":[131],"revealing":[132],"pattern":[136],"drivers.":[140],"Comprehensive":[141],"experiments":[142],"real-word":[145],"data":[146],"set":[147],"collected":[148],"from":[149],"New":[151],"York":[152],"City":[153],"clearly":[154],"validate":[155],"effectiveness":[157],"our":[159],"proposed":[160],"predicting":[163],"behaviors,":[167],"also":[169],"support":[170],"hypothesis":[172],"factors":[175],"indeed":[176],"predictability":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
