{"id":"https://openalex.org/W3080827759","doi":"https://doi.org/10.1145/3394486.3403281","title":"Polestar","display_name":"Polestar","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3080827759","doi":"https://doi.org/10.1145/3394486.3403281","mag":"3080827759"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & 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/A5100458897","display_name":"Hao Liu","orcid":"https://orcid.org/0000-0003-4271-1567"},"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":"Hao Liu","raw_affiliation_strings":["Baidu Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research, Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414502","display_name":"Ying Li","orcid":"https://orcid.org/0009-0007-8100-6568"},"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":"Ying Li","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032187620","display_name":"Yanjie Fu","orcid":"https://orcid.org/0000-0002-1767-8024"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanjie Fu","raw_affiliation_strings":["University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015257178","display_name":"Huaibo Mei","orcid":null},"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":"Huaibo Mei","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101481194","display_name":"Jingbo Zhou","orcid":"https://orcid.org/0000-0003-2677-7021"},"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":"Jingbo Zhou","raw_affiliation_strings":["Baidu Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research, Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031836304","display_name":"Xu Ma","orcid":"https://orcid.org/0000-0003-2012-9808"},"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":"Xu Ma","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"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 University, Newark, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, Newark, NJ, 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":null,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2321","last_page":"2329"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998999834060669,"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":0.9998999834060669,"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/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"}},{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.993399977684021,"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/public-transport","display_name":"Public transport","score":0.7521820068359375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6856446862220764},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.574802041053772},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5557109713554382},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5379872918128967},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.4263456165790558},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.37363654375076294},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1970815658569336},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.16906490921974182},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.1595485806465149},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10556477308273315}],"concepts":[{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.7521820068359375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6856446862220764},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.574802041053772},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5557109713554382},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5379872918128967},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4263456165790558},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.37363654375076294},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1970815658569336},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.16906490921974182},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.1595485806465149},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10556477308273315}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3403281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W805408692","https://openalex.org/W1503398984","https://openalex.org/W1559814459","https://openalex.org/W1936915774","https://openalex.org/W2031674781","https://openalex.org/W2037403365","https://openalex.org/W2072699031","https://openalex.org/W2091635795","https://openalex.org/W2097268493","https://openalex.org/W2131676173","https://openalex.org/W2146583842","https://openalex.org/W2167432060","https://openalex.org/W2169178923","https://openalex.org/W2181401341","https://openalex.org/W2181494072","https://openalex.org/W2263919949","https://openalex.org/W2290289666","https://openalex.org/W2295598076","https://openalex.org/W2397633064","https://openalex.org/W2744457212","https://openalex.org/W2781191210","https://openalex.org/W2904403013","https://openalex.org/W2950883684","https://openalex.org/W2952254630","https://openalex.org/W2952785130","https://openalex.org/W2953071387","https://openalex.org/W2997513934","https://openalex.org/W3034326350","https://openalex.org/W3102476541"],"related_works":["https://openalex.org/W2188500270","https://openalex.org/W2303858293","https://openalex.org/W2915512527","https://openalex.org/W51364034","https://openalex.org/W2798997222","https://openalex.org/W2798198862","https://openalex.org/W2091548507","https://openalex.org/W2368816706","https://openalex.org/W3159414774","https://openalex.org/W4385728102"],"abstract_inverted_index":{"Public":[0,88],"transportation":[1,16,37,62,81,95],"plays":[2],"a":[3,73,86,111,132,193],"critical":[4],"role":[5],"in":[6,48,67,97,158,166],"people's":[7],"daily":[8],"life.":[9],"It":[10],"has":[11,170],"been":[12,171],"proven":[13],"that":[14],"public":[15,61,80,94],"is":[17,186],"more":[18,40],"environmentally":[19],"sustainable,":[20],"efficient,":[21],"and":[22,39,78,163,200],"economical":[23],"than":[24],"any":[25],"other":[26],"forms":[27],"of":[28,36,99,156,160,177,196,204],"travel.":[29],"However,":[30],"due":[31],"to":[32,58,92,138],"the":[33,51,154,178],"increasing":[34],"expansion":[35],"networks":[38],"complex":[41],"travel":[42,101,144],"situations,":[43],"people":[44],"are":[45],"having":[46],"difficulties":[47],"efficiently":[49],"finding":[50],"most":[52],"preferred":[53],"route":[54,113,125,134],"from":[55],"one":[56,176],"place":[57],"another":[59],"through":[60],"systems.":[63],"To":[64,183],"this":[65,68],"end,":[66],"paper,":[69],"we":[70,83,109,130],"present":[71],"Polestar,":[72],"data-driven":[74],"engine":[75],"for":[76,123],"intelligent":[77],"efficient":[79,119,124],"routing.Specifically,":[82],"first":[84],"propose":[85,131],"novel":[87],"Transportation":[89],"Graph":[90],"(PTG)":[91],"model":[93],"system":[96],"terms":[98,159],"various":[100],"costs,":[102],"such":[103],"as":[104],"time":[105],"or":[106],"distance.":[107],"Then,":[108],"introduce":[110],"general":[112],"search":[114],"algorithm":[115],"coupled":[116],"with":[117],"an":[118],"station":[120],"binding":[121],"method":[122],"candidate":[126,135],"generation.":[127],"After":[128],"that,":[129],"two-pass":[133],"ranking":[136],"module":[137],"capture":[139],"user":[140,205],"preferences":[141],"under":[142],"dynamic":[143],"situations.":[145],"Finally,":[146],"experiments":[147],"on":[148,173],"two":[149],"real-world":[150],"data":[151],"sets":[152],"demonstrate":[153],"advantages":[155],"Polestar":[157,169,185],"both":[161],"efficiency":[162],"effectivenes":[164],"Indeed,":[165],"early":[167],"2019,":[168],"deployed":[172],"Baidu":[174],"Maps,":[175],"world's":[179],"largest":[180],"map":[181],"services.":[182],"date,":[184],"servicing":[187],"over":[188,192],"330":[189],"cities,":[190],"answers":[191],"hundred":[194],"millions":[195],"queries":[197],"each":[198],"day,":[199],"achieves":[201],"substantial":[202],"improvement":[203],"click":[206],"ratio.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2020-09-01T00:00:00"}