{"id":"https://openalex.org/W4379193102","doi":"https://doi.org/10.29007/5t69","title":"Scalable Probabilistic Routes","display_name":"Scalable Probabilistic Routes","publication_year":2023,"publication_date":"2023-06-03","ids":{"openalex":"https://openalex.org/W4379193102","doi":"https://doi.org/10.29007/5t69"},"language":"en","primary_location":{"id":"doi:10.29007/5t69","is_oa":true,"landing_page_url":"http://dx.doi.org/10.29007/5t69","pdf_url":"https://easychair.org/publications/open/k25n","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://easychair.org/publications/open/k25n","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023598179","display_name":"Suwei Yang","orcid":"https://orcid.org/0000-0003-1082-724X"},"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":true,"raw_author_name":"Suwei Yang","raw_affiliation_strings":["GrabTaxi Holdings, Singapore","National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"GrabTaxi Holdings, Singapore","institution_ids":[]},{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113770951","display_name":"Victor Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Victor Liang","raw_affiliation_strings":["GrabTaxi Holdings, Singapore"],"affiliations":[{"raw_affiliation_string":"GrabTaxi Holdings, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041528950","display_name":"Kuldeep S. Meel","orcid":"https://orcid.org/0000-0001-9423-5270"},"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":"Kuldeep S. Meel","raw_affiliation_strings":["National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023598179"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05134399,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"94","issue":null,"first_page":"457","last_page":"440"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9782000184059143,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9542999863624573,"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":0.7965041399002075},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7652515769004822},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5867094993591309},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5506842732429504},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5243309140205383},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4468459188938141},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43491923809051514},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.42484840750694275},{"id":"https://openalex.org/keywords/influence-diagram","display_name":"Influence diagram","score":0.419376939535141},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38455116748809814},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3357950448989868},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2846224308013916},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2710994482040405},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.24879467487335205}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7965041399002075},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7652515769004822},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5867094993591309},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5506842732429504},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5243309140205383},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4468459188938141},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43491923809051514},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.42484840750694275},{"id":"https://openalex.org/C20837028","wikidata":"https://www.wikidata.org/wiki/Q623966","display_name":"Influence diagram","level":3,"score":0.419376939535141},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38455116748809814},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3357950448989868},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2846224308013916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2710994482040405},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.24879467487335205},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.29007/5t69","is_oa":true,"landing_page_url":"http://dx.doi.org/10.29007/5t69","pdf_url":"https://easychair.org/publications/open/k25n","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2306.10736","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.10736","pdf_url":"https://arxiv.org/pdf/2306.10736","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.29007/5t69","is_oa":true,"landing_page_url":"http://dx.doi.org/10.29007/5t69","pdf_url":"https://easychair.org/publications/open/k25n","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320698","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4379193102.pdf","grobid_xml":"https://content.openalex.org/works/W4379193102.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W142212369","https://openalex.org/W1500231891","https://openalex.org/W1920501755","https://openalex.org/W1970696407","https://openalex.org/W1990249463","https://openalex.org/W2013473339","https://openalex.org/W2040370888","https://openalex.org/W2080267935","https://openalex.org/W2084243923","https://openalex.org/W2132022337","https://openalex.org/W2133527541","https://openalex.org/W2143083884","https://openalex.org/W2160365857","https://openalex.org/W2226456780","https://openalex.org/W2402839980","https://openalex.org/W2486886792","https://openalex.org/W2598550376","https://openalex.org/W2750925158","https://openalex.org/W2753132782","https://openalex.org/W2788694654","https://openalex.org/W2809128166","https://openalex.org/W2904507620","https://openalex.org/W2966429551","https://openalex.org/W2970971581","https://openalex.org/W3017049286","https://openalex.org/W3034506759","https://openalex.org/W3098821697","https://openalex.org/W3099451540","https://openalex.org/W3099878876","https://openalex.org/W3124320616","https://openalex.org/W3125143580","https://openalex.org/W4231934124","https://openalex.org/W4245630182","https://openalex.org/W4295312788","https://openalex.org/W4381568526"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W2163814182","https://openalex.org/W3143712745","https://openalex.org/W2160610433"],"abstract_inverted_index":{"Inference":[0],"and":[1,21,29,42,87],"prediction":[2,35],"of":[3,7,32,63,70,77,108,115,127,133,166,173],"routes":[4,50,168],"have":[5],"become":[6],"interest":[8],"over":[9],"the":[10,25,30,61,68,71,78,113,125,158,164],"past":[11],"decade":[12],"owing":[13,82],"to":[14,83,112,122,177],"a":[15,100,105,118,134,140,151],"dramatic":[16],"increase":[17],"in":[18,117],"package":[19],"delivery":[20],"ride-sharing":[22],"services.":[23],"Given":[24],"underlying":[26],"combinatorial":[27],"structure":[28],"incorporation":[31],"probabilities,":[33],"route":[34,144],"involves":[36],"techniques":[37],"from":[38,150],"both":[39],"formal":[40],"methods":[41],"machine":[43],"learning.":[44],"One":[45],"promising":[46],"approach":[47,65,79],"for":[48],"predicting":[49],"uses":[51,104],"decision":[52,73,129],"diagrams":[53],"that":[54,103,157],"are":[55,95],"augmented":[56],"with":[57,110],"probability":[58],"values.":[59],"However,":[60],"effectiveness":[62],"this":[64,91],"depends":[66],"on":[67],"size":[69,126],"compiled":[72],"diagrams.":[74,130],"The":[75],"scalability":[76],"is":[80],"limited":[81],"its":[84],"empirical":[85],"runtime":[86],"space":[88],"complexity.":[89],"In":[90,146],"work,":[92],"our":[93,147],"contributions":[94],"two-fold:":[96],"first,":[97],"we":[98,138,155],"introduce":[99],"relaxed":[101],"encoding":[102],"linear":[106],"number":[107,114],"variables":[109],"respect":[111],"vertices":[116],"road":[119,153],"network":[120],"graph":[121],"significantly":[123],"reduce":[124],"resultant":[128],"Secondly,":[131],"instead":[132],"stepwise":[135],"sampling":[136],"procedure,":[137],"propose":[139],"single":[141],"pass":[142],"sampling-based":[143],"prediction.":[145],"evaluations":[148],"arising":[149],"real-world":[152],"network,":[154],"demonstrate":[156],"resulting":[159],"system":[160],"achieves":[161],"around":[162],"twice":[163],"quality":[165],"suggested":[167],"while":[169],"being":[170],"an":[171],"order":[172],"magnitude":[174],"faster":[175],"compared":[176],"state-of-the-art.":[178]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
