{"id":"https://openalex.org/W2071242924","doi":"https://doi.org/10.1109/mdm.2010.40","title":"Efficient Evaluation of k-Range Nearest Neighbor Queries in Road Networks","display_name":"Efficient Evaluation of k-Range Nearest Neighbor Queries in Road Networks","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2071242924","doi":"https://doi.org/10.1109/mdm.2010.40","mag":"2071242924"},"language":"en","primary_location":{"id":"doi:10.1109/mdm.2010.40","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mdm.2010.40","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Eleventh International Conference on Mobile Data Management","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/A5060363706","display_name":"Jie Bao","orcid":"https://orcid.org/0000-0002-5642-1993"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jie Bao","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022507249","display_name":"Chi-Yin Chow","orcid":"https://orcid.org/0000-0002-9566-0743"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chi-Yin Chow","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007454642","display_name":"Mohamed F. Mokbel","orcid":"https://orcid.org/0000-0002-6686-1757"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed F. Mokbel","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001457193","display_name":"Wei\u2010Shinn Ku","orcid":"https://orcid.org/0000-0001-8636-4689"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei-Shinn Ku","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Aubum University, Auburn, AL, USA","Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Aubum University, Auburn, AL, USA","institution_ids":["https://openalex.org/I82497590"]},{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA#TAB#","institution_ids":["https://openalex.org/I82497590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5060363706"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":5.7491,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.96595961,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"115","last_page":"124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":1.0,"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":1.0,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/computer-science","display_name":"Computer science","score":0.839837908744812},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.7929073572158813},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.7380880117416382},{"id":"https://openalex.org/keywords/range-query","display_name":"Range query (database)","score":0.6845983266830444},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.561983048915863},{"id":"https://openalex.org/keywords/online-aggregation","display_name":"Online aggregation","score":0.519811749458313},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.511179506778717},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5079596638679504},{"id":"https://openalex.org/keywords/spatial-query","display_name":"Spatial query","score":0.45150575041770935},{"id":"https://openalex.org/keywords/sargable","display_name":"Sargable","score":0.3778441846370697},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35628873109817505},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.30254197120666504},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.2909846305847168},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.175689697265625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13668936491012573}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.839837908744812},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7929073572158813},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7380880117416382},{"id":"https://openalex.org/C136736807","wikidata":"https://www.wikidata.org/wiki/Q818943","display_name":"Range query (database)","level":5,"score":0.6845983266830444},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.561983048915863},{"id":"https://openalex.org/C24028149","wikidata":"https://www.wikidata.org/wiki/Q7094056","display_name":"Online aggregation","level":5,"score":0.519811749458313},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.511179506778717},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5079596638679504},{"id":"https://openalex.org/C172722865","wikidata":"https://www.wikidata.org/wiki/Q2302053","display_name":"Spatial query","level":5,"score":0.45150575041770935},{"id":"https://openalex.org/C192939062","wikidata":"https://www.wikidata.org/wiki/Q104840822","display_name":"Sargable","level":4,"score":0.3778441846370697},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35628873109817505},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.30254197120666504},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2909846305847168},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.175689697265625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13668936491012573},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mdm.2010.40","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mdm.2010.40","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Eleventh International Conference on Mobile Data Management","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.212.875","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.212.875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.umn.edu/~mokbel/papers/mdm10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1511415058","https://openalex.org/W1537417465","https://openalex.org/W1543003006","https://openalex.org/W1796251476","https://openalex.org/W1861819370","https://openalex.org/W1975246472","https://openalex.org/W1975293494","https://openalex.org/W1982735015","https://openalex.org/W2002471647","https://openalex.org/W2007695015","https://openalex.org/W2011318858","https://openalex.org/W2074149673","https://openalex.org/W2076395037","https://openalex.org/W2089959302","https://openalex.org/W2101024939","https://openalex.org/W2106936040","https://openalex.org/W2112469755","https://openalex.org/W2118291925","https://openalex.org/W2127151074","https://openalex.org/W2143709779","https://openalex.org/W2146905023","https://openalex.org/W2163820446","https://openalex.org/W2164454204","https://openalex.org/W2169336598","https://openalex.org/W2171901130","https://openalex.org/W4285719527","https://openalex.org/W6630687699","https://openalex.org/W6638215252","https://openalex.org/W6639269622","https://openalex.org/W6652201950","https://openalex.org/W6669007072","https://openalex.org/W6673414462","https://openalex.org/W6684190996","https://openalex.org/W6684302118"],"related_works":["https://openalex.org/W3125756434","https://openalex.org/W1560919561","https://openalex.org/W2096359267","https://openalex.org/W2889903446","https://openalex.org/W185198413","https://openalex.org/W2150741898","https://openalex.org/W2901901036","https://openalex.org/W2156905243","https://openalex.org/W2184296057","https://openalex.org/W1793997780"],"abstract_inverted_index":{"A":[0],"k-Range":[1],"Nearest":[2],"Neighbor":[3],"(or":[4],"kRNN":[5,35,94,121],"for":[6,40,93],"short)":[7],"query":[8,27,36,102,122,157,175,192,210],"in":[9,43,125,173,189],"road":[10,22],"networks":[11],"finds":[12],"the":[13,21,31,50,66,90,98,138,156,161,166,174,186,196,206,209,214],"k":[14],"nearest":[15],"neighbors":[16,170],"of":[17,191],"every":[18],"point":[19],"on":[20,30],"segments":[23],"within":[24],"a":[25,61,86,109,132,145,153],"given":[26],"region":[28],"based":[29],"network":[32],"distance.":[33],"The":[34,177],"is":[37,53,58,68,83,200],"significantly":[38],"important":[39],"location-based":[41],"applications":[42],"many":[44],"realistic":[45],"scenarios.":[46],"For":[47],"example,":[48],"(1)":[49,130],"user\u2019s":[51,56,167],"location":[52,57,75,82],"uncertain,":[54],"i.e.,":[55,80],"modeled":[59],"by":[60],"spatial":[62,87],"region,":[63],"and":[64,142,160,195,213],"(2)":[65,143],"user":[67],"not":[69],"willing":[70],"to":[71,76,136,151,204],"reveal":[72],"her":[73,78,81],"exact":[74,168],"preserve":[77],"privacy,":[79],"blurred":[84],"into":[85],"region.":[88],"However,":[89],"existing":[91,187],"solutions":[92],"queries":[95],"simply":[96],"apply":[97],"traditional":[99],"k-nearest":[100,169],"neighbor":[101],"processing":[103,123,158],"algorithm":[104,124,129,183],"multiple":[105],"times,":[106],"which":[107],"poses":[108],"huge":[110],"redundant":[111,139],"searching":[112,140],"overhead.":[113,216],"To":[114],"this":[115,126],"end,":[116],"we":[117],"propose":[118],"an":[119,201],"efficient":[120],"paper.":[127],"Our":[128],"employs":[131],"shared":[133],"execution":[134],"approach":[135],"eliminate":[137],"overhead,":[141,163],"provides":[144],"parameter":[146,199],"that":[147,181],"can":[148],"be":[149],"tuned":[150],"achieve":[152,205],"tradeoff":[154,207],"between":[155,208],"performance":[159],"storage":[162,215],"while":[164],"guaranteeing":[165],"are":[171],"included":[172],"answers.":[176],"experimental":[178],"results":[179],"show":[180],"our":[182],"always":[184],"outperforms":[185],"solution":[188],"terms":[190],"response":[193,211],"time,":[194],"introduced":[197],"tuning":[198],"effective":[202],"way":[203],"time":[212]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":7}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}