{"id":"https://openalex.org/W3174077323","doi":"https://doi.org/10.1145/3448016.3459245","title":"P2H: Efficient Distance Querying on Road Networks by Projected Vertex Separators","display_name":"P2H: Efficient Distance Querying on Road Networks by Projected Vertex Separators","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3174077323","doi":"https://doi.org/10.1145/3448016.3459245","mag":"3174077323"},"language":"en","primary_location":{"id":"doi:10.1145/3448016.3459245","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448016.3459245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","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/A5101806437","display_name":"Zitong Chen","orcid":"https://orcid.org/0000-0001-6054-2782"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zitong Chen","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110164824","display_name":"Ada Wai-Chee Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ada Wai-Chee Fu","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065607065","display_name":"Minhao Jiang","orcid":"https://orcid.org/0000-0002-9007-7225"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minhao Jiang","raw_affiliation_strings":["TuSimple, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"TuSimple, San Diego, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011148671","display_name":"Eric Lo","orcid":"https://orcid.org/0000-0003-2679-3945"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Eric Lo","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100426105","display_name":"Pengfei Zhang","orcid":"https://orcid.org/0000-0002-5776-519X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Zhang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101806437"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":2.6159,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.9042953,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"313","last_page":"325"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9869999885559082,"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"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.8197331428527832},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7329802513122559},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4693727493286133},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4686673879623413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40383362770080566},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3729422390460968},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3375365734100342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16990509629249573},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.10427349805831909}],"concepts":[{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.8197331428527832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7329802513122559},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4693727493286133},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4686673879623413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40383362770080566},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3729422390460968},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3375365734100342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16990509629249573},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.10427349805831909},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3448016.3459245","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448016.3459245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W30435042","https://openalex.org/W1493214567","https://openalex.org/W1553945535","https://openalex.org/W1969483458","https://openalex.org/W1982943597","https://openalex.org/W1989894867","https://openalex.org/W2002838096","https://openalex.org/W2005945380","https://openalex.org/W2071362870","https://openalex.org/W2093455937","https://openalex.org/W2096304152","https://openalex.org/W2101282805","https://openalex.org/W2112513979","https://openalex.org/W2116437000","https://openalex.org/W2116793595","https://openalex.org/W2142126162","https://openalex.org/W2146583842","https://openalex.org/W2148831787","https://openalex.org/W2159394589","https://openalex.org/W2169528473","https://openalex.org/W2257437291","https://openalex.org/W2474823404","https://openalex.org/W2579664199","https://openalex.org/W2588514192","https://openalex.org/W2764587448","https://openalex.org/W2791658191","https://openalex.org/W2798620495","https://openalex.org/W2912492336","https://openalex.org/W2948227434","https://openalex.org/W2967996808","https://openalex.org/W2970568805","https://openalex.org/W2982996625","https://openalex.org/W3008629102","https://openalex.org/W3032255305","https://openalex.org/W3161610145","https://openalex.org/W4255388013"],"related_works":["https://openalex.org/W2380059383","https://openalex.org/W4224278052","https://openalex.org/W2063679720","https://openalex.org/W2031856784","https://openalex.org/W2018218513","https://openalex.org/W2185495545","https://openalex.org/W2075046161","https://openalex.org/W2385335131","https://openalex.org/W2067481825","https://openalex.org/W2064938438"],"abstract_inverted_index":{"The":[0],"most":[1],"efficient":[2,99],"known":[3,103],"approach":[4],"for":[5,61,64],"shortest":[6],"distance":[7],"querying":[8],"on":[9,70],"road":[10,73],"networks":[11,74],"is":[12,25,95],"via":[13],"a":[14],"tree":[15],"decomposition":[16],"based":[17],"2-hop":[18],"labeling":[19],"index.":[20],"A":[21],"major":[22],"challenge":[23],"here":[24],"how":[26],"to":[27],"reduce":[28,80],"the":[29,34,44,81,101],"query":[30,86],"time":[31,87],"by":[32],"reducing":[33],"label":[35,83],"size.":[36],"To":[37],"this":[38],"end,":[39],"we":[40],"propose":[41],"P2H":[42,77,94],"with":[43],"novel":[45],"ideas":[46],"of":[47,54],"projected":[48],"vertex":[49,55],"separators":[50],"and":[51,85],"optimized":[52],"selection":[53],"separators.":[56],"We":[57],"also":[58],"introduce":[59],"mechanisms":[60],"index":[62],"maintenance":[63],"edge":[65],"weight":[66],"updating.":[67],"Our":[68],"experiments":[69],"multiple":[71],"real":[72],"show":[75],"that":[76],"can":[78],"greatly":[79],"effective":[82],"sizes":[84],"over":[88],"existing":[89],"algorithms.":[90],"For":[91],"larger":[92],"datasets,":[93],"around":[96],"twice":[97],"as":[98,100],"best":[102],"algorithm.":[104]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}