{"id":"https://openalex.org/W1936915774","doi":"https://doi.org/10.1109/icde.2015.7113313","title":"Personalized route recommendation using big trajectory data","display_name":"Personalized route recommendation using big trajectory data","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1936915774","doi":"https://doi.org/10.1109/icde.2015.7113313","mag":"1936915774"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2015.7113313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-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/A5101891868","display_name":"Jian Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Dai","raw_affiliation_strings":["Institute of Software, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072309548","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0002-1658-1079"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["Department of Computer Science, Aalborg University, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084021933","display_name":"Chenjuan Guo","orcid":"https://orcid.org/0000-0002-4516-4637"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Chenjuan Guo","raw_affiliation_strings":["Department of Computer Science, Aarhus University, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aarhus University, Denmark","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057841485","display_name":"Zhiming Ding","orcid":"https://orcid.org/0000-0002-2057-5325"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiming Ding","raw_affiliation_strings":["Institute of Software, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101891868"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128818","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":15.6343,"has_fulltext":false,"cited_by_count":201,"citation_normalized_percentile":{"value":0.99431688,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"543","last_page":"554"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9995999932289124,"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":0.9962000250816345,"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/computer-science","display_name":"Computer science","score":0.7592355012893677},{"id":"https://openalex.org/keywords/taxis","display_name":"Taxis","score":0.7339800596237183},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5868262648582458},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.5836954116821289},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.5752965211868286},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.501225471496582},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47775354981422424},{"id":"https://openalex.org/keywords/self-driving","display_name":"Self driving","score":0.4283861219882965},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3332376480102539},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.26597505807876587},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1180189847946167},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10892415046691895},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10521906614303589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7592355012893677},{"id":"https://openalex.org/C183373512","wikidata":"https://www.wikidata.org/wiki/Q949618","display_name":"Taxis","level":2,"score":0.7339800596237183},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5868262648582458},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.5836954116821289},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.5752965211868286},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.501225471496582},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47775354981422424},{"id":"https://openalex.org/C3018391801","wikidata":"https://www.wikidata.org/wiki/Q741490","display_name":"Self driving","level":2,"score":0.4283861219882965},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3332376480102539},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.26597505807876587},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1180189847946167},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10892415046691895},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10521906614303589},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icde.2015.7113313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/a5b35f83-48fb-44bf-8804-9f389be131eb","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/a5b35f83-48fb-44bf-8804-9f389be131eb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Dai , J , Yang , B , Guo , C & Ding , Z 2015 , Personalized route recommendation using big trajectory data . in 31st IEEE International Conference on Data Engineering, ICDE 2015, Seoul, South Korea, April 13-17, 2015 . IEEE , pp. 543-554 , IEEE 31st International Conference on Data Engineering (ICDE) , Seoul , Korea, Republic of , 13/04/2015 . https://doi.org/10.1109/ICDE.2015.7113313","raw_type":"bookPart"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.5699999928474426,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W96330011","https://openalex.org/W153377290","https://openalex.org/W1500231891","https://openalex.org/W1515242458","https://openalex.org/W1587948386","https://openalex.org/W1663973292","https://openalex.org/W1973968359","https://openalex.org/W1990336586","https://openalex.org/W2005854848","https://openalex.org/W2012778686","https://openalex.org/W2014005999","https://openalex.org/W2014478203","https://openalex.org/W2023279748","https://openalex.org/W2031674781","https://openalex.org/W2039423859","https://openalex.org/W2069069662","https://openalex.org/W2085248615","https://openalex.org/W2097268493","https://openalex.org/W2101823987","https://openalex.org/W2111160151","https://openalex.org/W2123838014","https://openalex.org/W2135822894","https://openalex.org/W2155044259","https://openalex.org/W4212863985","https://openalex.org/W4411440035","https://openalex.org/W6606215200","https://openalex.org/W6630034672"],"related_works":["https://openalex.org/W2731640799","https://openalex.org/W3145095895","https://openalex.org/W2594548639","https://openalex.org/W4387544810","https://openalex.org/W2978498151","https://openalex.org/W2782837293","https://openalex.org/W1946755446","https://openalex.org/W2388377527","https://openalex.org/W565532978","https://openalex.org/W2372614270"],"abstract_inverted_index":{"When":[0],"planning":[1],"routes,":[2,121],"drivers":[3,20,91],"usually":[4,57],"consider":[5],"a":[6,64,130,139,162,204],"multitude":[7],"of":[8,83,101,129,132,161,221],"different":[9,23,35,105],"travel":[10,14,53,66,116],"costs,":[11],"e.g.,":[12],"distances,":[13],"times,":[15],"and":[16,29,55,103,142,146,225,231],"fuel":[17],"consumption.":[18],"Different":[19],"may":[21,33],"choose":[22],"routes":[24,61,71,88],"between":[25],"the":[26,59,69,73,81,110,143,151,159,171,177,181,187,191,195,199,218,222],"same":[27,60],"source":[28],"destination":[30],"because":[31],"they":[32,228],"have":[34],"driving":[36,40,107],"preferences":[37,108],"(e.g.,":[38,68],"time-efficient":[39],"v.s.":[41],"fuel-efficient":[42],"driving).":[43],"However,":[44],"existing":[45],"routing":[46],"services":[47],"support":[48],"little":[49],"in":[50,190,213],"modeling":[51,102],"multiple":[52,115],"costs":[54],"personalization-they":[56],"deliver":[58],"that":[62,125,157,227],"minimize":[63],"single":[65],"cost":[67],"shortest":[70,188],"or":[72],"fastest":[74],"routes)":[75],"to":[76,85,89,138,175,198],"all":[77,135],"drivers.":[78],"We":[79],"study":[80],"problem":[82],"how":[84,170],"recommend":[86,119,186],"personalized":[87,120,196],"individual":[90],"using":[92],"big":[93],"trajectory":[94,207],"data.":[95],"First,":[96],"we":[97,122,154,185],"provide":[98,123,155],"techniques":[99,124,156,224],"capable":[100],"updating":[104],"drivers'":[106,111],"from":[109,134,210],"trajectories":[112,133,136],"while":[113],"considering":[114],"costs.":[117],"To":[118],"enable":[126,158],"efficient":[127,230],"selection":[128],"subset":[131],"according":[137],"driver's":[140],"preference":[141],"source,":[144],"destination,":[145],"departure":[147],"time":[148],"specified":[149],"by":[150],"driver.":[152,200],"Next,":[153],"construction":[160],"small":[163,192],"graph":[164,193],"with":[165,203],"appropriate":[166],"edge":[167],"weights":[168],"reflecting":[169],"driver":[172],"would":[173],"like":[174],"use":[176],"edges":[178],"based":[179],"on":[180],"selected":[182],"trajectories.":[183],"Finally,":[184],"route":[189,197],"as":[194],"Empirical":[201],"studies":[202],"large,":[205],"real":[206],"data":[208],"set":[209],"52,211":[211],"taxis":[212],"Beijing":[214],"offer":[215],"insight":[216],"into":[217],"design":[219],"properties":[220],"proposed":[223],"suggest":[226],"are":[229],"effective.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":36},{"year":2018,"cited_by_count":23},{"year":2017,"cited_by_count":18},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}