{"id":"https://openalex.org/W2888406937","doi":"https://doi.org/10.1142/s0218488518500344","title":"A Novel Model for Mining Frequent Patterns Based on Embedded Granular Computing","display_name":"A Novel Model for Mining Frequent Patterns Based on Embedded Granular Computing","publication_year":2018,"publication_date":"2018-08-21","ids":{"openalex":"https://openalex.org/W2888406937","doi":"https://doi.org/10.1142/s0218488518500344","mag":"2888406937"},"language":"en","primary_location":{"id":"doi:10.1142/s0218488518500344","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218488518500344","pdf_url":null,"source":{"id":"https://openalex.org/S69518169","display_name":"International Journal of Uncertainty Fuzziness and Knowledge-Based Systems","issn_l":"0218-4885","issn":["0218-4885","1793-6411"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems","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/A5071245512","display_name":"Gang Fang","orcid":"https://orcid.org/0000-0002-2462-9124"},"institutions":[{"id":"https://openalex.org/I50180762","display_name":"Chongqing Three Gorges University","ror":"https://ror.org/05rs3pv16","country_code":"CN","type":"education","lineage":["https://openalex.org/I50180762"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gang Fang","raw_affiliation_strings":["Chongqing Three Gorges University, Wanzhou, Chongqing, 404020, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing Three Gorges University, Wanzhou, Chongqing, 404020, P. R. China","institution_ids":["https://openalex.org/I50180762"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375441","display_name":"Jiale Wang","orcid":"https://orcid.org/0009-0004-3213-8167"},"institutions":[{"id":"https://openalex.org/I50180762","display_name":"Chongqing Three Gorges University","ror":"https://ror.org/05rs3pv16","country_code":"CN","type":"education","lineage":["https://openalex.org/I50180762"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiale Wang","raw_affiliation_strings":["Chongqing Three Gorges University, Wanzhou, Chongqing, 404020, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing Three Gorges University, Wanzhou, Chongqing, 404020, P. R. China","institution_ids":["https://openalex.org/I50180762"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046688147","display_name":"Ying Hong","orcid":"https://orcid.org/0000-0002-6602-6276"},"institutions":[{"id":"https://openalex.org/I50180762","display_name":"Chongqing Three Gorges University","ror":"https://ror.org/05rs3pv16","country_code":"CN","type":"education","lineage":["https://openalex.org/I50180762"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Ying","raw_affiliation_strings":["Chongqing Three Gorges University, Wanzhou, Chongqing, 404020, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing Three Gorges University, Wanzhou, Chongqing, 404020, P. R. China","institution_ids":["https://openalex.org/I50180762"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5071245512"],"corresponding_institution_ids":["https://openalex.org/I50180762"],"apc_list":null,"apc_paid":null,"fwci":0.206,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55521985,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"26","issue":"05","first_page":"741","last_page":"769"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998999834060669,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9997000098228455,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/granular-computing","display_name":"Granular computing","score":0.8821945190429688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.783706784248352},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7025421857833862},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.5205384492874146},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.44933104515075684},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.24442216753959656},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.13768354058265686}],"concepts":[{"id":"https://openalex.org/C17209119","wikidata":"https://www.wikidata.org/wiki/Q5596712","display_name":"Granular computing","level":3,"score":0.8821945190429688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.783706784248352},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7025421857833862},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.5205384492874146},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.44933104515075684},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.24442216753959656},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.13768354058265686},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218488518500344","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218488518500344","pdf_url":null,"source":{"id":"https://openalex.org/S69518169","display_name":"International Journal of Uncertainty Fuzziness and Knowledge-Based Systems","issn_l":"0218-4885","issn":["0218-4885","1793-6411"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8225759298","display_name":null,"funder_award_id":"61602072","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1512234690","https://openalex.org/W1976128998","https://openalex.org/W1991800357","https://openalex.org/W2025051375","https://openalex.org/W2034589438","https://openalex.org/W2050620801","https://openalex.org/W2069907550","https://openalex.org/W2100406636","https://openalex.org/W2125220820","https://openalex.org/W2138080682","https://openalex.org/W3156834475"],"related_works":["https://openalex.org/W2390733913","https://openalex.org/W3010178579","https://openalex.org/W2294857909","https://openalex.org/W2400358292","https://openalex.org/W2347951170","https://openalex.org/W128746893","https://openalex.org/W2373679199","https://openalex.org/W2613635421","https://openalex.org/W2064873764","https://openalex.org/W2367639718"],"abstract_inverted_index":{"For":[0],"mining":[1,11,27,41,49,58,78,99,224,241],"frequent":[2,53,119,242],"patterns,":[3,54,120],"it":[4,125,148,181],"is":[5,66,106,115,231],"very":[6],"expensive":[7],"for":[8,51,240],"the":[9,15,25,36,69,73,97,122,128,133,139,145,150,154,158,163,171,175,184,193,197,204,207,222,255,259],"Apriori":[10,70],"model":[12,28,50,59,71,79,105,114,201,225,260],"to":[13,34,214],"read":[14],"database":[16,129],"repeatedly,":[17],"and":[18,72,83,137,180,234],"a":[19,46,56,211,262],"highly":[20],"condensed":[21],"data":[22,40,48,57,77,98,167,223],"structure":[23,168],"made":[24],"FP-growth":[26,74],"cost":[29],"larger":[30],"memory.":[31],"In":[32],"order":[33],"avoid":[35],"disadvantages":[37],"of":[38,142,166,173,206,248,258,264],"these":[39,237,245],"model,":[42,100],"this":[43,109],"paper":[44],"proposes":[45],"novel":[47],"discovering":[52,118],"called":[55],"based":[60,226],"on":[61,121,144,227],"embedded":[62,102,198,228],"granular":[63,86,103,112,199,229],"computing,":[64,87],"which":[65,88],"different":[67,92,246],"from":[68,85,210],"model.":[75],"The":[76,111],"adopts":[80],"efficiently":[81],"dividing":[82],"conquering":[84],"can":[89,161,182],"construct":[90],"adaptively":[91],"hierarchical":[93],"granules.":[94],"To":[95],"form":[96],"an":[101,251],"computing":[104,113,186,200,230],"proposed":[107],"in":[108,117],"paper.":[110],"used":[116],"one":[123],"hand,":[124,147],"avoids":[126],"reading":[127],"repeatedly":[130],"via":[131,192],"constructing":[132],"extended":[134],"information":[135],"granule,":[136,156,195],"lessen":[138],"calculated":[140],"amount":[141],"support;":[143],"other":[146],"reduces":[149],"memory":[151,164],"requirements":[152],"by":[153,261],"attribute":[155,194],"where":[157],"search":[159,208],"space":[160,165,209],"compress":[162],"that":[169,221],"make":[170],"method":[172],"generating":[174],"candidate":[176],"become":[177],"simple":[178],"relatively;":[179],"divide":[183],"overlarge":[185],"task":[187],"into":[188],"several":[189,215],"easy":[190],"operations":[191],"namely,":[196],"could":[202],"short":[203],"size":[205],"super":[212],"state":[213],"sub-states.":[216],"All":[217],"experimental":[218],"results":[219],"show":[220],"more":[232],"reasonable":[233],"efficient":[235],"than":[236],"classical":[238],"models":[239],"patterns":[243],"under":[244],"types":[247],"datasets.":[249],"Otherwise,":[250],"extra":[252],"discussion":[253],"describes":[254],"performance":[256],"trend":[257],"group":[263],"experiments.":[265]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}