{"id":"https://openalex.org/W2984598834","doi":"https://doi.org/10.1145/3357384.3357927","title":"Path Travel Time Estimation using Attribute-related Hybrid Trajectories Network","display_name":"Path Travel Time Estimation using Attribute-related Hybrid Trajectories Network","publication_year":2019,"publication_date":"2019-11-03","ids":{"openalex":"https://openalex.org/W2984598834","doi":"https://doi.org/10.1145/3357384.3357927","mag":"2984598834"},"language":"en","primary_location":{"id":"doi:10.1145/3357384.3357927","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3357927","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","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/A5106746347","display_name":"Xi Lin","orcid":"https://orcid.org/0000-0001-5303-1191"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xi Lin","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029640741","display_name":"Yequan Wang","orcid":"https://orcid.org/0000-0001-7530-6125"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yequan Wang","raw_affiliation_strings":["Tencent Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Inc., Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010903591","display_name":"Xiaokui Xiao","orcid":"https://orcid.org/0000-0003-0914-4580"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xiaokui Xiao","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103063766","display_name":"Zengxiang Li","orcid":"https://orcid.org/0000-0002-2455-2462"},"institutions":[{"id":"https://openalex.org/I3004594783","display_name":"Institute of High Performance Computing","ror":"https://ror.org/02n0ejh50","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3004594783","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zengxiang Li","raw_affiliation_strings":["Institute of High Performance Computing, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of High Performance Computing, Singapore, Singapore","institution_ids":["https://openalex.org/I3004594783"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061002947","display_name":"Sourav S. Bhowmick","orcid":"https://orcid.org/0000-0003-1957-8016"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Sourav S. Bhowmick","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2689,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.9375,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1973","last_page":"1982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9983999729156494,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.8814998269081116},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7454819679260254},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5759190320968628},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4935258626937866},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.49271872639656067},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.459816038608551},{"id":"https://openalex.org/keywords/urban-computing","display_name":"Urban computing","score":0.45241448283195496},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43047699332237244},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3527781665325165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2557039260864258},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.246376633644104},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12960204482078552},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09611126780509949}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8814998269081116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7454819679260254},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5759190320968628},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4935258626937866},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.49271872639656067},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.459816038608551},{"id":"https://openalex.org/C2778459138","wikidata":"https://www.wikidata.org/wiki/Q7900107","display_name":"Urban computing","level":2,"score":0.45241448283195496},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43047699332237244},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3527781665325165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2557039260864258},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.246376633644104},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12960204482078552},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09611126780509949},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3357384.3357927","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3357927","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G4196627310","display_name":null,"funder_award_id":"MOE2015-T2-2-069","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"}],"funders":[{"id":"https://openalex.org/F4320320698","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49"},{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W832618888","https://openalex.org/W1686810756","https://openalex.org/W1832693441","https://openalex.org/W2047332899","https://openalex.org/W2064675550","https://openalex.org/W2069069662","https://openalex.org/W2075364600","https://openalex.org/W2097117768","https://openalex.org/W2116140262","https://openalex.org/W2133564696","https://openalex.org/W2144475703","https://openalex.org/W2156387975","https://openalex.org/W2176412452","https://openalex.org/W2194775991","https://openalex.org/W2419272040","https://openalex.org/W2528639018","https://openalex.org/W2562607067","https://openalex.org/W2572984335","https://openalex.org/W2573698050","https://openalex.org/W2583466634","https://openalex.org/W2623769582","https://openalex.org/W2766836212","https://openalex.org/W2768348081","https://openalex.org/W2778869053","https://openalex.org/W2786780230","https://openalex.org/W2788997482","https://openalex.org/W2809623940","https://openalex.org/W2897079037","https://openalex.org/W2900001365","https://openalex.org/W2910952060","https://openalex.org/W2913340405","https://openalex.org/W2949767467","https://openalex.org/W2952740813","https://openalex.org/W2963001155"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W3131574667","https://openalex.org/W2126194848","https://openalex.org/W3001431193","https://openalex.org/W2955605379","https://openalex.org/W3212670299","https://openalex.org/W4366491531","https://openalex.org/W2904515274","https://openalex.org/W2024348445","https://openalex.org/W4320024144"],"abstract_inverted_index":{"Estimation":[0],"of":[1,82,88,118,125,146,184,189,192,213],"path":[2,136,186],"travel":[3,137,187,218],"time":[4,188,219],"provides":[5],"great":[6],"value":[7],"to":[8,32,39,59,63,102,180],"applications":[9],"like":[10],"bus":[11,53,66],"line":[12],"designs":[13],"and":[14,142,170,221],"route":[15],"plannings.":[16],"Existing":[17],"approaches":[18],"are":[19,27,131],"mainly":[20],"based":[21],"on":[22,229],"single-source":[23,74],"trajectory":[24,75,86,107,120,175,197,231],"datasets":[25],"that":[26,159,199,223],"usually":[28,56],"large":[29],"in":[30,68,208],"size":[31],"ensure":[33],"a":[34,69,119,156,181,190,195],"satisfactory":[35],"performance.":[36],"This":[37],"leads":[38],"two":[40],"limitations:":[41],"1)":[42],"Large-scale":[43],"data":[44,54,61,76,216],"may":[45],"not":[46,113],"always":[47],"be":[48],"attainable,":[49],"e.g.":[50,85],"city-scale":[51],"public":[52],"is":[55,100],"small":[57],"compared":[58],"taxi":[60],"due":[62],"relative":[64],"fewer":[65],"trips":[67],"day.":[70],"2)":[71],"Considering":[72],"only":[73],"neglects":[77],"the":[78,94,115,135,143,162,168,211],"potential":[79],"estimation-improving":[80],"insights":[81],"external":[83],"data,":[84],"dataset":[87,198],"other":[89,106,203],"vehicle":[90,122,204],"sources":[91],"obtained":[92],"from":[93,202],"same":[95],"geographical":[96],"region.":[97],"A":[98],"challenge":[99],"how":[101],"effectively":[103,160],"utilize":[104],"such":[105],"sources.":[108],"Moreover,":[109],"existing":[110],"work":[111],"does":[112],"attend":[114],"important":[116,132],"attributes":[117],"including":[121],"ID,":[123],"day":[124],"week,":[126],"rainfall":[127],"level":[128],"etc.,":[129],"which":[130],"for":[133,217],"estimating":[134,185],"time.":[138],"Motivated":[139],"by":[140],"these":[141],"recent":[144],"successes":[145],"neural":[147,157],"network":[148],"models,":[149],"we":[150],"propose":[151],"Attribute-related":[152],"Hybrid":[153],"Trajectories":[154],"Network~(AtHy-TNet),":[155],"model":[158],"utilizes":[161],"attribute":[163],"correlations,":[164],"as":[165,167],"well":[166],"spatial":[169],"temporal":[171],"relationships":[172],"across":[173],"hybrid":[174,196,215],"data.":[176],"We":[177,206],"apply":[178],"this":[179],"novel":[182],"problem":[183],"type":[191],"vehicles":[193],"using":[194],"includes":[200],"trajectories":[201],"types.":[205],"demonstrate":[207],"our":[209],"experiments":[210],"benefits":[212],"considering":[214],"estimation,":[220],"show":[222],"AtHy-TNet":[224],"significantly":[225],"outperforms":[226],"state-of-the-art":[227],"methods":[228],"real-world":[230],"datasets.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}