{"id":"https://openalex.org/W2037605480","doi":"https://doi.org/10.1145/2093973.2094001","title":"Multi-approximate-keyword routing in GIS data","display_name":"Multi-approximate-keyword routing in GIS data","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2037605480","doi":"https://doi.org/10.1145/2093973.2094001","mag":"2037605480"},"language":"en","primary_location":{"id":"doi:10.1145/2093973.2094001","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2093973.2094001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","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/A5100757927","display_name":"Bin Yao","orcid":"https://orcid.org/0000-0002-6478-4209"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Yao","raw_affiliation_strings":["Shanghai JiaoTong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai JiaoTong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034060974","display_name":"Mingwang Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingwang Tang","raw_affiliation_strings":["School of Computing, University of Utah","[ School of Computing, University of Utah]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, University of Utah","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"[ School of Computing, University of Utah]","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100450462","display_name":"Li Fei-Fei","orcid":"https://orcid.org/0000-0002-7481-0810"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feifei Li","raw_affiliation_strings":["School of Computing, University of Utah","[ School of Computing, University of Utah]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, University of Utah","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"[ School of Computing, University of Utah]","institution_ids":["https://openalex.org/I223532165"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1847,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.87977074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"201","last_page":"210"},"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9830999970436096,"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/computer-science","display_name":"Computer science","score":0.7502771615982056},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7131093740463257},{"id":"https://openalex.org/keywords/shortest-path-problem","display_name":"Shortest path problem","score":0.6848303079605103},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.6410068273544312},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4799795150756836},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.4676700830459595},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4387194514274597},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3970695734024048},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.31333911418914795},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2140929400920868},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1785585582256317},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12024343013763428}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7502771615982056},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7131093740463257},{"id":"https://openalex.org/C22590252","wikidata":"https://www.wikidata.org/wiki/Q1058754","display_name":"Shortest path problem","level":3,"score":0.6848303079605103},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.6410068273544312},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4799795150756836},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.4676700830459595},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4387194514274597},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3970695734024048},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.31333911418914795},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2140929400920868},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1785585582256317},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12024343013763428},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2093973.2094001","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2093973.2094001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.231.8164","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.8164","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.utah.edu/%7Elifeifei/papers/makrgis.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G5758755102","display_name":null,"funder_award_id":"IIS-0916488","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1829285201","https://openalex.org/W1990974055","https://openalex.org/W1995074666","https://openalex.org/W2000879295","https://openalex.org/W2006307108","https://openalex.org/W2014889099","https://openalex.org/W2089326542","https://openalex.org/W2096725637","https://openalex.org/W2126455549","https://openalex.org/W2140048308","https://openalex.org/W2151345349","https://openalex.org/W2155801378","https://openalex.org/W2165735734","https://openalex.org/W2167847032","https://openalex.org/W2169336598","https://openalex.org/W2752885492","https://openalex.org/W2946046356","https://openalex.org/W3145128584","https://openalex.org/W7029321148"],"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/W1983399550","https://openalex.org/W97075385","https://openalex.org/W2357523926"],"abstract_inverted_index":{"For":[0],"GIS":[1,116],"data":[2],"situated":[3],"on":[4,27,114,140,149],"a":[5,12,168],"road":[6,150],"network,":[7],"shortest":[8,40,59],"path":[9,41,60],"search":[10,42],"is":[11,55,94],"basic":[13],"operation.":[14],"In":[15,118],"practice,":[16],"however,":[17],"users":[18],"are":[19],"often":[20],"interested":[21],"at":[22,64],"routing":[23,77],"when":[24,106],"certain":[25],"constraints":[26],"the":[28,38,53,58,75,88,100,171],"textual":[29],"information":[30],"have":[31],"been":[32],"also":[33,161],"incorporated.":[34],"This":[35],"work":[36],"complements":[37],"standard":[39],"with":[43,152],"multiple":[44],"keywords":[45,93],"and":[46,84,130,158],"an":[47],"approximate":[48,85,122,165],"string":[49],"similarity":[50],"function,":[51],"where":[52],"goal":[54],"to":[56,145],"find":[57],"that":[61,163],"passes":[62],"through":[63],"least":[65],"one":[66,164],"matching":[67],"object":[68],"per":[69],"keyword;":[70],"we":[71],"dub":[72],"this":[73,119],"problem":[74],"multi-approximate-keyword":[76],"(MAKR)":[78],"query.":[79],"We":[80,160],"present":[81],"both":[82],"exact":[83,101],"solutions.":[86],"When":[87],"number":[89],"\u03ba":[90,97,107],"of":[91,154,156],"query":[92,126],"small":[95],"(e.g.,":[96],"\u2264":[98],"6),":[99],"solution":[102],"works":[103],"efficiently.":[104],"However,":[105],"increases,":[108],"it":[109],"becomes":[110],"increasingly":[111],"expensive":[112],"(especially":[113],"large":[115],"data).":[117],"case,":[120],"our":[121,137],"methods":[123],"achieve":[124],"superb":[125],"efficiency,":[127],"excellent":[128],"scalability,":[129],"high":[131],"approximation":[132],"quality,":[133],"as":[134],"indicated":[135],"in":[136,170],"extensive":[138],"experiments":[139],"large,":[141],"real":[142],"datasets":[143],"(up":[144],"2":[146],"million":[147],"points":[148],"networks":[151],"hundreds":[153],"thousands":[155],"nodes":[157],"edges).":[159],"prove":[162],"method":[166],"has":[167],"\u03ba-approximation":[169],"worst":[172],"case.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}