{"id":"https://openalex.org/W2797815898","doi":"https://doi.org/10.3390/ijgi7040146","title":"A Method of Mining Association Rules for Geographical Points of Interest","display_name":"A Method of Mining Association Rules for Geographical Points of Interest","publication_year":2018,"publication_date":"2018-04-10","ids":{"openalex":"https://openalex.org/W2797815898","doi":"https://doi.org/10.3390/ijgi7040146","mag":"2797815898"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi7040146","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi7040146","pdf_url":"https://www.mdpi.com/2220-9964/7/4/146/pdf?version=1525347952","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/7/4/146/pdf?version=1525347952","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006880080","display_name":"Shiwei Lian","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiwei Lian","raw_affiliation_strings":["School of Geographic Spatial Information, University of Information Engineering, Zhengzhou 450000, China","The Unit 31682 of Lanzhou, Lanzhou 730000, China"],"affiliations":[{"raw_affiliation_string":"School of Geographic Spatial Information, University of Information Engineering, Zhengzhou 450000, China","institution_ids":["https://openalex.org/I169689159"]},{"raw_affiliation_string":"The Unit 31682 of Lanzhou, Lanzhou 730000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101034849","display_name":"Jinning Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jinning Gao","raw_affiliation_strings":["The Unit 31682 of Lanzhou, Lanzhou 730000, China"],"affiliations":[{"raw_affiliation_string":"The Unit 31682 of Lanzhou, Lanzhou 730000, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061295171","display_name":"Hongwei Li","orcid":"https://orcid.org/0000-0001-6231-4126"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]},{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Li","raw_affiliation_strings":["Intellectual City Research Institute of Zhengzhou University, Zhengzhou 450000, China","School of Geographic Spatial Information, University of Information Engineering, Zhengzhou 450000, China"],"affiliations":[{"raw_affiliation_string":"Intellectual City Research Institute of Zhengzhou University, Zhengzhou 450000, China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"School of Geographic Spatial Information, University of Information Engineering, Zhengzhou 450000, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101034849"],"corresponding_institution_ids":[],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.4102,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70160128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":"4","first_page":"146","last_page":"146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":1.0,"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"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9926000237464905,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.8240711688995361},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7217460870742798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6560852527618408},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.5999347567558289},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.5479916334152222},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4762996435165405},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.4707289934158325},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43658214807510376},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.43584150075912476},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.31949883699417114},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2448047697544098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18188011646270752},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10167449712753296}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.8240711688995361},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7217460870742798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6560852527618408},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.5999347567558289},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.5479916334152222},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4762996435165405},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.4707289934158325},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43658214807510376},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.43584150075912476},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.31949883699417114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2448047697544098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18188011646270752},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10167449712753296},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/ijgi7040146","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi7040146","pdf_url":"https://www.mdpi.com/2220-9964/7/4/146/pdf?version=1525347952","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ef1ffc3ae9a44c9887f245ae31ebb408","is_oa":true,"landing_page_url":"https://doaj.org/article/ef1ffc3ae9a44c9887f245ae31ebb408","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information, Vol 7, Iss 4, p 146 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2220-9964/7/4/146/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/ijgi7040146","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information; Volume 7; Issue 4; Pages: 146","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/ijgi7040146","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi7040146","pdf_url":"https://www.mdpi.com/2220-9964/7/4/146/pdf?version=1525347952","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5062941083","display_name":null,"funder_award_id":"41571394","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2797815898.pdf","grobid_xml":"https://content.openalex.org/works/W2797815898.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W80315153","https://openalex.org/W1508643881","https://openalex.org/W1574241439","https://openalex.org/W1577527731","https://openalex.org/W1584197556","https://openalex.org/W1587655595","https://openalex.org/W1673310716","https://openalex.org/W1968259950","https://openalex.org/W1982621401","https://openalex.org/W1983506100","https://openalex.org/W1987212347","https://openalex.org/W2000106226","https://openalex.org/W2001812280","https://openalex.org/W2007043321","https://openalex.org/W2016287391","https://openalex.org/W2024511949","https://openalex.org/W2032237967","https://openalex.org/W2032469362","https://openalex.org/W2032929146","https://openalex.org/W2036752235","https://openalex.org/W2041211425","https://openalex.org/W2046893834","https://openalex.org/W2047404088","https://openalex.org/W2048433053","https://openalex.org/W2053029294","https://openalex.org/W2059464296","https://openalex.org/W2078174680","https://openalex.org/W2094344174","https://openalex.org/W2100176599","https://openalex.org/W2110893883","https://openalex.org/W2115482638","https://openalex.org/W2128517606","https://openalex.org/W2128817530","https://openalex.org/W2140116260","https://openalex.org/W2146712929","https://openalex.org/W2166559705","https://openalex.org/W2166778517","https://openalex.org/W2169474320","https://openalex.org/W2998574808","https://openalex.org/W3124607078","https://openalex.org/W3215701813","https://openalex.org/W4243450781","https://openalex.org/W4252403066","https://openalex.org/W6602452485","https://openalex.org/W6628750762","https://openalex.org/W6631810562","https://openalex.org/W6674967761","https://openalex.org/W6675462168","https://openalex.org/W6684584758"],"related_works":["https://openalex.org/W3163639875","https://openalex.org/W2364999035","https://openalex.org/W1986811679","https://openalex.org/W2113309085","https://openalex.org/W2410549043","https://openalex.org/W3014936414","https://openalex.org/W2394010168","https://openalex.org/W2993700121","https://openalex.org/W2184109998","https://openalex.org/W2362772308"],"abstract_inverted_index":{"Association":[0],"rule":[1,72,183],"(AR)":[2],"mining":[3],"represents":[4],"a":[5,19,93,111,189],"challenge":[6],"in":[7,82,109],"the":[8,52,57,76,80,83,126,140,152,158,181,186,192,199],"field":[9],"of":[10,22,54,62,116,128,191],"data":[11],"mining.":[12],"Mining":[13],"ARs":[14],"using":[15],"traditional":[16],"algorithms":[17],"generates":[18],"large":[20],"number":[21],"candidate":[23],"rules,":[24],"and":[25,36,45,74,124,156,175],"even":[26],"if":[27],"we":[28,68],"use":[29],"binding":[30],"measures":[31],"such":[32],"as":[33],"support,":[34],"reliability,":[35],"lift,":[37],"there":[38],"are":[39,48],"still":[40],"several":[41],"rules":[42,53,123,193],"to":[43,50,106,121,150,168,179,196],"keep,":[44],"domain":[46],"experts":[47],"needed":[49],"extract":[51],"interest":[55,154],"from":[56],"remaining":[58],"rules.":[59,84],"The":[60,133],"focus":[61],"this":[63,90],"paper":[64,91],"is":[65,119,135,148,166,177,194],"on":[66,103,185],"whether":[67,198],"can":[69],"directly":[70],"provide":[71],"rankings":[73],"calculate":[75],"proportional":[77],"relationship":[78],"between":[79],"items":[81,129],"To":[85],"address":[86],"these":[87],"two":[88,200],"questions,":[89],"proposes":[92],"modified":[94],"FP-Growth":[95,100],"algorithm":[96,101,147],"called":[97,114],"FP-GCID":[98,165],"(novel":[99],"based":[102,184],"Cluster":[104],"IDs)":[105],"generate":[107,169],"ARs;":[108],"addition,":[110],"new":[112],"method":[113],"Mean-Product":[115],"Probabilities":[117],"(MPP)":[118],"proposed":[120],"rank":[122],"compute":[125],"proportion":[127],"for":[130],"one":[131],"rule.":[132],"experiment":[134],"divided":[136],"into":[137,161],"three":[138],"phases:":[139],"DBSCAN":[141],"(Density-Based":[142],"Scanning":[143],"Algorithm":[144],"with":[145],"Noise)":[146],"used":[149,167,178,195],"cluster":[151,173],"geographic":[153],"points":[155],"map":[157],"obtained":[159],"clusters":[160],"corresponding":[162],"transaction":[163],"data;":[164],"ARs,":[170],"which":[171],"contain":[172],"information;":[174],"MPP":[176],"choose":[180],"best":[182],"rankings.":[187],"Finally,":[188],"visualization":[190],"validate":[197],"previously":[201],"stated":[202],"requirements":[203],"were":[204],"fulfilled.":[205]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
