{"id":"https://openalex.org/W2010335233","doi":"https://doi.org/10.1145/2346496.2346514","title":"Towards fine-grained urban traffic knowledge extraction using mobile sensing","display_name":"Towards fine-grained urban traffic knowledge extraction using mobile sensing","publication_year":2012,"publication_date":"2012-08-12","ids":{"openalex":"https://openalex.org/W2010335233","doi":"https://doi.org/10.1145/2346496.2346514","mag":"2010335233"},"language":"en","primary_location":{"id":"doi:10.1145/2346496.2346514","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2346496.2346514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM SIGKDD International Workshop on Urban 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/A5087213835","display_name":"Xuegang Ban","orcid":"https://orcid.org/0000-0003-3605-971X"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuegang (Jeff) Ban","raw_affiliation_strings":["CEE, Rensselaer Polytechnic Institute, Troy, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CEE, Rensselaer Polytechnic Institute, Troy, NY","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078160983","display_name":"Marco Gruteser","orcid":"https://orcid.org/0000-0002-7424-4951"},"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":"Marco Gruteser","raw_affiliation_strings":["WINLAB, Rutgers University, North Brunswick, NJ","WINLAB, Rutgers University, North Brunswick, NJ#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"WINLAB, Rutgers University, North Brunswick, NJ","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"WINLAB, Rutgers University, North Brunswick, NJ#TAB#","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.3853,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.97709552,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9983000159263611,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.6565696597099304},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5528393983840942}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6565696597099304},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5528393983840942},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2346496.2346514","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2346496.2346514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM SIGKDD International Workshop on Urban Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.261.101","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.261.101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.winlab.rutgers.edu/%7Egruteser/papers/urbTraffic_v12.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.706.1196","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.706.1196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://csce.uark.edu/%7Etingxiny/courses/5013sp14/reading/Ban2012TFU2346496.2346514.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2571536587","display_name":null,"funder_award_id":"CMMI-1031452CMMI-1055555CMMI-1031400CNS-0845896","funder_id":"https://openalex.org/F4320337388","funder_display_name":"Division of Computer and Network Systems"},{"id":"https://openalex.org/G7183112478","display_name":null,"funder_award_id":"CMMI-1031452CMMI-1055555CMMI-1031400CNS-0845896","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308074","display_name":"New York State Department of Transportation","ror":"https://ror.org/04bbkwf42"},{"id":"https://openalex.org/F4320337388","display_name":"Division of Computer and Network Systems","ror":"https://ror.org/02rdzmk74"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W578585133","https://openalex.org/W647128556","https://openalex.org/W811954167","https://openalex.org/W1980258017","https://openalex.org/W1980801609","https://openalex.org/W1982300822","https://openalex.org/W1984961057","https://openalex.org/W1985986451","https://openalex.org/W1992477951","https://openalex.org/W2000854095","https://openalex.org/W2024649066","https://openalex.org/W2031674781","https://openalex.org/W2059356865","https://openalex.org/W2093921901","https://openalex.org/W2097225206","https://openalex.org/W2101823987","https://openalex.org/W2103151433","https://openalex.org/W2103968250","https://openalex.org/W2122169437","https://openalex.org/W2126236329","https://openalex.org/W2130482380","https://openalex.org/W2139212933","https://openalex.org/W2143319963","https://openalex.org/W2163359022","https://openalex.org/W2167339613","https://openalex.org/W2169991130","https://openalex.org/W2172041433","https://openalex.org/W2953145849","https://openalex.org/W3193477162","https://openalex.org/W6675676514","https://openalex.org/W6684984388"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655","https://openalex.org/W2359140296"],"abstract_inverted_index":{"We":[0,78],"introduce":[1],"our":[2],"vision":[3],"for":[4,43,68,123,127],"mining":[5],"fine-grained":[6],"urban":[7,128],"traffic":[8,24,49,61,72,102,109,125],"knowledge":[9,126],"from":[10],"mobile":[11,29,96],"sensing,":[12],"especially":[13],"GPS":[14],"location":[15],"traces.":[16],"Beyond":[17],"characterizing":[18],"human":[19],"mobility":[20],"patterns":[21],"and":[22,59,71,93,111],"measuring":[23],"congestion,":[25],"we":[26],"show":[27],"how":[28],"sensing":[30],"can":[31,74],"also":[32],"reveal":[33],"details":[34],"such":[35,52],"as":[36],"intersection":[37],"performance":[38],"statistics":[39],"that":[40,65],"are":[41,117],"useful":[42],"optimizing":[44],"the":[45,66,84,95],"timing":[46],"of":[47,108],"a":[48],"signal.":[50],"Realizing":[51],"applications":[53],"requires":[54],"co-designing":[55],"privacy":[56,69,80],"protection":[57],"algorithms":[58,81],"novel":[60],"modeling":[62,73,103],"techniques":[63,104],"so":[64],"needs":[67],"preserving":[70],"be":[75,99],"simultaneously":[76],"satisfied.":[77],"explore":[79],"based":[82],"on":[83],"virtual":[85],"trip":[86],"lines":[87],"(VTL)":[88],"concept":[89],"to":[90],"regulate":[91],"where":[92],"when":[94],"data":[97],"should":[98],"collected.":[100],"The":[101,114],"feature":[105],"an":[106],"integration":[107],"principles":[110],"learning/optimization":[112],"techniques.":[113],"proposed":[115],"methods":[116],"illustrated":[118],"using":[119],"two":[120],"case":[121],"studies":[122],"extracting":[124],"signalized":[129],"intersection.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
