{"id":"https://openalex.org/W3135304967","doi":"https://doi.org/10.3233/ida-195071","title":"A parametric approximation algorithm for spatial group keyword queries","display_name":"A parametric approximation algorithm for spatial group keyword queries","publication_year":2021,"publication_date":"2021-03-04","ids":{"openalex":"https://openalex.org/W3135304967","doi":"https://doi.org/10.3233/ida-195071","mag":"3135304967"},"language":"en","primary_location":{"id":"doi:10.3233/ida-195071","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-195071","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-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/A5025839344","display_name":"Jincao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jincao Li","raw_affiliation_strings":["Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041210918","display_name":"Ming Xu","orcid":"https://orcid.org/0000-0001-9332-5258"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Xu","raw_affiliation_strings":["Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041210918"],"corresponding_institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":1.1977,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77806353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"25","issue":"2","first_page":"305","last_page":"319"},"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.9932000041007996,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7785664200782776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7284597158432007},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.6081884503364563},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5235830545425415},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47990545630455017},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4705125689506531},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4461294412612915},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.41424012184143066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19882461428642273},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.19178563356399536}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7785664200782776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7284597158432007},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.6081884503364563},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5235830545425415},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47990545630455017},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4705125689506531},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4461294412612915},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.41424012184143066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19882461428642273},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.19178563356399536},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-195071","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-195071","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W9061855","https://openalex.org/W1694364829","https://openalex.org/W1985694287","https://openalex.org/W1991128947","https://openalex.org/W2006307108","https://openalex.org/W2009411756","https://openalex.org/W2045622468","https://openalex.org/W2046144220","https://openalex.org/W2063319420","https://openalex.org/W2074495191","https://openalex.org/W2101903378","https://openalex.org/W2118269922","https://openalex.org/W2140048308","https://openalex.org/W2151345349","https://openalex.org/W2160128361","https://openalex.org/W2165735734","https://openalex.org/W2343414189","https://openalex.org/W2561011558","https://openalex.org/W2594240107","https://openalex.org/W2788051057","https://openalex.org/W2901596760","https://openalex.org/W2937111329","https://openalex.org/W2970604792","https://openalex.org/W3003570628","https://openalex.org/W3037571924","https://openalex.org/W4242599275","https://openalex.org/W4246472747","https://openalex.org/W6600364960"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W2121910908"],"abstract_inverted_index":{"With":[0],"the":[1,26,36,40,43,85,93,120,127,152],"application":[2],"of":[3,21,73,84,87,151],"big":[4],"data,":[5],"various":[6],"queries":[7,15],"arise":[8],"for":[9,62,108],"information":[10],"retrieval.":[11],"Spatial":[12],"group":[13],"keyword":[14],"aim":[16],"to":[17,57,92,98,129,144],"find":[18],"a":[19,31,77,100,110,117],"set":[20],"spatial":[22],"objects":[23,41],"that":[24],"cover":[25],"query":[27,44,132],"keywords":[28],"and":[29,42,54,71,123,149],"minimize":[30],"goal":[32,90,95],"function":[33],"such":[34],"as":[35],"total":[37],"distance":[38],"between":[39,119],"point.":[45],"This":[46],"problem":[47,65],"is":[48,55],"widely":[49],"found":[50],"in":[51,137],"database":[52],"applications":[53],"known":[56],"be":[58],"NP-hard.":[59],"Efficient":[60],"algorithms":[61,75],"solving":[63],"this":[64],"can":[66],"only":[67],"provide":[68],"approximate":[69,89],"solutions,":[70],"most":[72],"these":[74],"achieve":[76],"fixed":[78],"approximation":[79,106,112,121],"ratio":[80,86,122],"(the":[81],"upper":[82],"bound":[83],"an":[88,105,138],"value":[91],"optimal":[94],"value).":[96],"Thus,":[97],"obtain":[99],"self-adjusting":[101],"algorithm,":[102],"we":[103],"propose":[104],"algorithm":[107,115,153],"achieving":[109],"parametric":[111],"ratio.":[113],"The":[114,147],"makes":[116],"trade-off":[118],"time":[124],"consumption":[125],"enabling":[126],"users":[128],"assign":[130],"arbitrary":[131],"accuracy.":[133],"Additionally,":[134],"it":[135,142],"runs":[136],"on-the-fly":[139],"manner,":[140],"making":[141],"scalable":[143],"large-scale":[145],"applications.":[146],"efficiency":[148],"scalability":[150],"were":[154],"further":[155],"validated":[156],"using":[157],"benchmark":[158],"datasets.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-25T06:16:34.145877","created_date":"2025-10-10T00:00:00"}
