{"id":"https://openalex.org/W2808959436","doi":"https://doi.org/10.1145/3219819.3220055","title":"Route Recommendations for Idle Taxi Drivers","display_name":"Route Recommendations for Idle Taxi Drivers","publication_year":2018,"publication_date":"2018-07-19","ids":{"openalex":"https://openalex.org/W2808959436","doi":"https://doi.org/10.1145/3219819.3220055","mag":"2808959436"},"language":"en","primary_location":{"id":"doi:10.1145/3219819.3220055","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3219819.3220055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery &amp; 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/A5008612767","display_name":"Nandani Garg","orcid":null},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nandani Garg","raw_affiliation_strings":["IIT Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054697900","display_name":"Sayan Ranu","orcid":"https://orcid.org/0000-0003-4147-9372"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sayan Ranu","raw_affiliation_strings":["IIT Delhi, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1425","last_page":"1434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9994000196456909,"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/T11106","display_name":"Data Management and Algorithms","score":0.9988999962806702,"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/T12288","display_name":"Optimization and Search Problems","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/idle","display_name":"Idle","score":0.7184213995933533},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6766179800033569},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.4863017499446869},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.47990497946739197},{"id":"https://openalex.org/keywords/customer-satisfaction","display_name":"Customer satisfaction","score":0.45411303639411926},{"id":"https://openalex.org/keywords/productivity","display_name":"Productivity","score":0.42611774802207947},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.3439920246601105},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24500033259391785},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.10747838020324707},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.08082479238510132},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07785776257514954},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.075958251953125}],"concepts":[{"id":"https://openalex.org/C16320812","wikidata":"https://www.wikidata.org/wiki/Q1812200","display_name":"Idle","level":2,"score":0.7184213995933533},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6766179800033569},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.4863017499446869},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.47990497946739197},{"id":"https://openalex.org/C191511416","wikidata":"https://www.wikidata.org/wiki/Q999278","display_name":"Customer satisfaction","level":2,"score":0.45411303639411926},{"id":"https://openalex.org/C204983608","wikidata":"https://www.wikidata.org/wiki/Q2111958","display_name":"Productivity","level":2,"score":0.42611774802207947},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3439920246601105},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24500033259391785},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.10747838020324707},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.08082479238510132},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07785776257514954},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.075958251953125},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3219819.3220055","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3219819.3220055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W26726511","https://openalex.org/W41554520","https://openalex.org/W1515851193","https://openalex.org/W1538548313","https://openalex.org/W1567097384","https://openalex.org/W1625390266","https://openalex.org/W1981239355","https://openalex.org/W2008814765","https://openalex.org/W2024021677","https://openalex.org/W2025766355","https://openalex.org/W2031674781","https://openalex.org/W2064621720","https://openalex.org/W2074739868","https://openalex.org/W2101823987","https://openalex.org/W2132968912","https://openalex.org/W2138198492","https://openalex.org/W2168405694","https://openalex.org/W2365906439","https://openalex.org/W2757649114"],"related_works":["https://openalex.org/W2974485871","https://openalex.org/W1577119738","https://openalex.org/W2908872315","https://openalex.org/W1600399803","https://openalex.org/W4235210722","https://openalex.org/W4388633481","https://openalex.org/W2994960476","https://openalex.org/W2049601620","https://openalex.org/W2070778588","https://openalex.org/W2796721958"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,13,16,26,29,38,46,93,125,128],"problem":[3],"of":[4,127],"route":[5,69],"recommendation":[6,70],"to":[7,28,34,58,83,96,121,132],"idle":[8],"taxi":[9,17,39,108],"drivers":[10],"such":[11,135],"that":[12,117],"distance":[14,27],"between":[15],"and":[18,41,51,61,113,130],"an":[19],"anticipated":[20,31],"customer":[21,32,54,99],"request":[22],"is":[23,101,119],"minimized.":[24],"Minimizing":[25,74],"next":[30],"leads":[33],"more":[35],"productivity":[36],"for":[37,45],"driver":[40],"less":[42],"waiting":[43],"time":[44],"customer.":[47],"To":[48],"anticipate":[49],"when":[50],"where":[52,92],"future":[53,98],"requests":[55,100],"are":[56],"likely":[57],"come":[59],"from":[60,110],"accordingly":[62],"recom-":[63],"mend":[64],"routes,":[65],"we":[66],"develop":[67],"a":[68,88],"engine":[71],"called":[72],"MDM:":[73],"Distance":[75],"through":[76],"Monte":[77],"Carlo":[78],"Tree":[79],"Search.":[80],"In":[81],"contrast":[82],"existing":[84],"techniques,":[85],"MDM":[86,118],"employs":[87],"continuous":[89],"learning":[90],"platform":[91],"underlying":[94],"model":[95],"predict":[97],"dynamically":[102],"updated.":[103],"Extensive":[104],"experiments":[105],"on":[106],"real":[107],"data":[109],"New":[111],"York":[112],"San":[114],"Francisco":[115],"reveal":[116],"up":[120],"70%":[122],"better":[123],"than":[124],"state":[126],"art":[129],"robust":[131],"anomalous":[133],"events":[134],"as":[136],"concerts,":[137],"sporting":[138],"events,":[139],"etc.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
