{"id":"https://openalex.org/W2793970239","doi":"https://doi.org/10.1080/13658816.2018.1434525","title":"Mining significant crisp-fuzzy spatial association rules","display_name":"Mining significant crisp-fuzzy spatial association rules","publication_year":2018,"publication_date":"2018-02-08","ids":{"openalex":"https://openalex.org/W2793970239","doi":"https://doi.org/10.1080/13658816.2018.1434525","mag":"2793970239"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2018.1434525","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2018.1434525","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/100743/1/Shi_Mining_Significant_Crisp-Fuzzy.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100644664","display_name":"Wenzhong Shi","orcid":"https://orcid.org/0000-0002-3886-7027"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wenzhong Shi","raw_affiliation_strings":["Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P.R. China"],"raw_orcid":"https://orcid.org/0000-0002-3886-7027","affiliations":[{"raw_affiliation_string":"Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P.R. China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065293267","display_name":"Anshu Zhang","orcid":"https://orcid.org/0000-0001-7158-8292"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Anshu Zhang","raw_affiliation_strings":["Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P.R. China"],"raw_orcid":"https://orcid.org/0000-0001-7158-8292","affiliations":[{"raw_affiliation_string":"Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P.R. China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058054791","display_name":"Geoffrey I. Webb","orcid":"https://orcid.org/0000-0001-9963-5169"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Geoffrey I. Webb","raw_affiliation_strings":["Faculty of Information Technology, Monash University, Clayton, Victoria, Australia"],"raw_orcid":"https://orcid.org/0000-0001-9963-5169","affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Monash University, Clayton, Victoria, Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065293267"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":2.8175,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.92449051,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"32","issue":"6","first_page":"1247","last_page":"1270"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T11106","display_name":"Data Management and Algorithms","score":0.9976000189781189,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9943000078201294,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7667677402496338},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.7076361775398254},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.691352903842926},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6379553079605103},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5492191910743713},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.5139917731285095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3098335266113281},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27501562237739563}],"concepts":[{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7667677402496338},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.7076361775398254},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.691352903842926},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6379553079605103},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5492191910743713},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.5139917731285095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3098335266113281},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27501562237739563},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1080/13658816.2018.1434525","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2018.1434525","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/100743","is_oa":true,"landing_page_url":"http://hdl.handle.net/10397/100743","pdf_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/100743/1/Shi_Mining_Significant_Crisp-Fuzzy.pdf","source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal/Magazine Article"},{"id":"pmh:oai:figshare.com:article/5873139","is_oa":true,"landing_page_url":"https://figshare.com/articles/dataset/Mining_significant_crisp-fuzzy_spatial_association_rules/5873139","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Dataset"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/77621","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/77621","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal/Magazine Article"},{"id":"doi:10.6084/m9.figshare.5873139.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.5873139.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/100743","is_oa":true,"landing_page_url":"http://hdl.handle.net/10397/100743","pdf_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/100743/1/Shi_Mining_Significant_Crisp-Fuzzy.pdf","source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal/Magazine Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1884754691","display_name":null,"funder_award_id":"2017YFB0503604","funder_id":"https://openalex.org/F4320309618","funder_display_name":"Ministry of Science and Technology"},{"id":"https://openalex.org/G3187046464","display_name":null,"funder_award_id":"2017YFB0503604","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4206280202","display_name":"\u53ef\u9760\u6027\u9065\u611f\u5f71\u50cf\u5206\u7c7b\u4e0e\u7a7a\u95f4\u5173\u8054\u5206\u6790\u7814\u7a76","funder_award_id":"41331175","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2793970239.pdf"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W99863437","https://openalex.org/W316664468","https://openalex.org/W1484413656","https://openalex.org/W1549565124","https://openalex.org/W1556507321","https://openalex.org/W1556674401","https://openalex.org/W1974557077","https://openalex.org/W1975289027","https://openalex.org/W1976845418","https://openalex.org/W1979683229","https://openalex.org/W1993983826","https://openalex.org/W2008881019","https://openalex.org/W2013906437","https://openalex.org/W2026621533","https://openalex.org/W2029283089","https://openalex.org/W2033314834","https://openalex.org/W2039682706","https://openalex.org/W2043229934","https://openalex.org/W2045816045","https://openalex.org/W2047813642","https://openalex.org/W2067273185","https://openalex.org/W2068269545","https://openalex.org/W2077698461","https://openalex.org/W2094974204","https://openalex.org/W2117827905","https://openalex.org/W2118722179","https://openalex.org/W2121044470","https://openalex.org/W2131175701","https://openalex.org/W2140549588","https://openalex.org/W2151280208","https://openalex.org/W2154663323","https://openalex.org/W2157028625","https://openalex.org/W2166205682","https://openalex.org/W2233664955","https://openalex.org/W2244325062","https://openalex.org/W2277972536","https://openalex.org/W2329660289","https://openalex.org/W2613789965","https://openalex.org/W2767775162","https://openalex.org/W2921659045","https://openalex.org/W2998778915","https://openalex.org/W3023428462","https://openalex.org/W4235234743","https://openalex.org/W4239624924","https://openalex.org/W4240152324","https://openalex.org/W4243731503","https://openalex.org/W4245878497","https://openalex.org/W4256170606","https://openalex.org/W4289709539","https://openalex.org/W4289866267","https://openalex.org/W4302597354","https://openalex.org/W4388743382","https://openalex.org/W4388771367","https://openalex.org/W6661988213"],"related_works":["https://openalex.org/W128746893","https://openalex.org/W2367573304","https://openalex.org/W2537030075","https://openalex.org/W2006971496","https://openalex.org/W4310720718","https://openalex.org/W2065998343","https://openalex.org/W2369717039","https://openalex.org/W2384676159","https://openalex.org/W2982449560","https://openalex.org/W2110683262"],"abstract_inverted_index":{"Spatial":[0],"association":[1],"rule":[2,48],"mining":[3,9],"(SARM)":[4],"is":[5,255],"an":[6],"important":[7],"data":[8,109,133,260],"task":[10],"for":[11,83,112,117,228,257],"understanding":[12],"implicit":[13],"and":[14,45,80,87,128,139,151,250,262],"sophisticated":[15],"interactions":[16],"in":[17,160,167],"spatial":[18,118,259],"data.":[19,130],"The":[20,70,120,131,154,171,199,212,231],"usefulness":[21],"of":[22,28,36,42,47,67,91,145,164,173,190,240,246],"SARM":[23,60,113,146,165,248],"results,":[24,249],"represented":[25],"as":[26],"sets":[27],"rules,":[29,37,44],"depends":[30],"on":[31,235],"their":[32],"reliability:":[33],"the":[34,40,65,84,98,102,143,162,202,243],"abundance":[35,172],"control":[38],"over":[39],"risk":[41,189],"spurious":[43,191,207],"accuracy":[46],"interestingness":[49],"measure":[50],"(RIM)":[51],"values.":[52],"This":[53],"study":[54,103,234],"presents":[55],"crisp-fuzzy":[56,247],"SARM,":[57,223],"a":[58,106],"novel":[59],"method":[61,71],"that":[62,201,252],"can":[63],"enhance":[64],"reliability":[66,144,163,245],"resultant":[68,174],"rules.":[69],"firstly":[72],"prunes":[73],"dubious":[74],"rules":[75,93,138,175,192,208],"using":[76,94,184],"statistically":[77,196],"sound":[78,197],"tests":[79],"crisp":[81,222],"supports":[82],"patterns":[85],"involved,":[86],"then":[88],"evaluates":[89],"RIMs":[90],"accepted":[92],"fuzzy":[95,108,186],"supports.":[96],"For":[97],"RIM":[99,140,213],"evaluation":[100],"stage,":[101],"also":[104,215],"proposes":[105],"Gaussian-curve-based":[107],"discretization":[110],"model":[111],"with":[114,136,183],"improved":[115,177,244],"design":[116],"semantics.":[119],"proposed":[121,155],"techniques":[122,156],"were":[123],"evaluated":[124],"by":[125,178,195,221],"both":[126],"synthetic":[127,132],"real-world":[129,232],"was":[134,176,193,209],"generated":[135],"predesigned":[137],"values,":[141],"thus":[142],"results":[147,166],"could":[148],"be":[149],"confidently":[150],"quantitatively":[152],"evaluated.":[153],"showed":[157],"high":[158],"efficacy":[159],"enhancing":[161],"all":[168],"three":[169],"aspects.":[170],"50%":[179,227],"or":[180],"more":[181],"compared":[182],"conventional":[185],"SARM.":[187],"Minimal":[188],"guaranteed":[194],"tests.":[198],"probability":[200],"entire":[203],"result":[204],"contained":[205],"any":[206],"below":[210],"1%.":[211],"values":[214],"avoided":[216],"large":[217],"positive":[218],"errors":[219],"committed":[220],"which":[224],"typically":[225],"exceeded":[226],"representative":[229],"RIMs.":[230],"case":[233],"New":[236],"York":[237],"City":[238],"points":[239],"interest":[241],"reconfirms":[242],"demonstrates":[251],"such":[253],"improvement":[254],"critical":[256],"practical":[258],"analytics":[261],"decision":[263],"support.":[264]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
