{"id":"https://openalex.org/W2771872556","doi":"https://doi.org/10.1109/igarss.2017.8128262","title":"An adaptive maximal co-location mining algorithm","display_name":"An adaptive maximal co-location mining algorithm","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2771872556","doi":"https://doi.org/10.1109/igarss.2017.8128262","mag":"2771872556"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2017.8128262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8128262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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/A5033279713","display_name":"Xiaojing Yao","orcid":"https://orcid.org/0000-0001-9745-3150"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaojing Yao","raw_affiliation_strings":["Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764100","display_name":"Dacheng Wang","orcid":"https://orcid.org/0009-0009-0640-566X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dacheng Wang","raw_affiliation_strings":["Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101507877","display_name":"Ling Peng","orcid":"https://orcid.org/0000-0003-2999-9252"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Peng","raw_affiliation_strings":["Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110512006","display_name":"Tianhe Chi","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianhe Chi","raw_affiliation_strings":["Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Lab of Spatial Information Integration, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033279713"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":0.1849,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.4823018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"5551","last_page":"5554"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9904999732971191,"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":0.9904999732971191,"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/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9276000261306763,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.6524587869644165},{"id":"https://openalex.org/keywords/algorithm-design","display_name":"Algorithm design","score":0.4370415210723877},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4205024540424347},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3488543629646301}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6524587869644165},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.4370415210723877},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4205024540424347},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3488543629646301}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2017.8128262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8128262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1921428968","https://openalex.org/W1964570589","https://openalex.org/W1967005434","https://openalex.org/W1973749534","https://openalex.org/W1985092552","https://openalex.org/W1992583634","https://openalex.org/W2136642200","https://openalex.org/W2316616015"],"related_works":["https://openalex.org/W2393888177","https://openalex.org/W2967268719","https://openalex.org/W2544423928","https://openalex.org/W2117183908","https://openalex.org/W2115794623","https://openalex.org/W3115392711","https://openalex.org/W2360264381","https://openalex.org/W2067173559","https://openalex.org/W1613730747","https://openalex.org/W2541389358"],"abstract_inverted_index":{"Spatial":[0],"co-location":[1,24,77,153],"pattern":[2],"mining":[3,25],"is":[4,32],"employed":[5],"to":[6,34,40,86,125],"identify":[7,41,126],"a":[8,110,117],"group":[9],"of":[10,15,55,93],"spatial":[11,21],"types,":[12],"the":[13,53,64,81,88,114,127,140,157],"instances":[14,43,59],"which":[16,101],"are":[17,105,149],"frequently":[18],"located":[19],"in":[20,44],"proximity.":[22],"Current":[23],"methods":[26,51],"have":[27],"two":[28,102],"limitations:":[29],"(1)":[30],"it":[31],"difficult":[33],"set":[35],"an":[36,45,74],"appropriate":[37],"proximity":[38],"threshold":[39],"close":[42],"unknown":[46],"region":[47],"and":[48,60,96],"(2)":[49],"those":[50],"neglect":[52],"effects":[54,62],"distance":[56],"values":[57],"between":[58],"far-instance":[61],"on":[63,121],"pattern's":[65],"significance.":[66],"To":[67],"address":[68],"these":[69,122],"problems,":[70],"this":[71],"paper":[72],"proposes":[73],"adaptive":[75],"maximal":[76],"(AMCM)":[78],"algorithm.":[79],"First,":[80],"algorithm":[82,115,141,158],"uses":[83],"Voronoi":[84],"diagram":[85],"extract":[87],"most":[89],"related":[90],"instance":[91],"pairs":[92],"different":[94],"types":[95],"their":[97],"normalized":[98],"distances,":[99],"from":[100,135],"distance-separating":[103,123],"parameters":[104,124],"adaptively":[106,143],"extracted":[107],"by":[108,151],"using":[109],"statistical":[111],"method.":[112],"Second,":[113],"employs":[116],"reward-based":[118],"verification":[119],"based":[120],"prevalent":[128],"patterns.":[129],"Our":[130],"tests":[131],"with":[132],"real":[133],"data":[134],"Beijing,":[136],"China,":[137],"demonstrate":[138],"that":[139,148],"can":[142],"gain":[144],"many":[145],"interesting":[146],"patterns":[147],"neglected":[150],"traditional":[152],"methods.":[154],"In":[155],"addition,":[156],"runs":[159],"quickly":[160],"for":[161],"large-scale":[162],"datasets.":[163]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}