{"id":"https://openalex.org/W2750024164","doi":"https://doi.org/10.1145/3105971.3108450","title":"Visual clustering-based apriori ARM methodology for obtaining quality association rules","display_name":"Visual clustering-based apriori ARM methodology for obtaining quality association rules","publication_year":2017,"publication_date":"2017-08-14","ids":{"openalex":"https://openalex.org/W2750024164","doi":"https://doi.org/10.1145/3105971.3108450","mag":"2750024164"},"language":"en","primary_location":{"id":"doi:10.1145/3105971.3108450","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3105971.3108450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Symposium on Visual Information Communication and Interaction","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/A5086422507","display_name":"Simon Fong","orcid":"https://orcid.org/0000-0002-1848-7246"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":true,"raw_author_name":"Simon Fong","raw_affiliation_strings":["University of Macau, Taipa, Macau SAR"],"affiliations":[{"raw_affiliation_string":"University of Macau, Taipa, Macau SAR","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020799472","display_name":"Robert P. Biuk\u2010Aghai","orcid":"https://orcid.org/0000-0002-3538-3318"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Robert P. Biuk-Aghai","raw_affiliation_strings":["University of Macau, Taipa, Macau SAR"],"affiliations":[{"raw_affiliation_string":"University of Macau, Taipa, Macau SAR","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081113625","display_name":"Scarlet Tin","orcid":null},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Scarlet Tin","raw_affiliation_strings":["University of Macau, Taipa, Macau SAR"],"affiliations":[{"raw_affiliation_string":"University of Macau, Taipa, Macau SAR","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086422507"],"corresponding_institution_ids":["https://openalex.org/I204512498"],"apc_list":null,"apc_paid":null,"fwci":0.9673,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.8264026,"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":"69","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9915000200271606,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9661999940872192,"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/association-rule-learning","display_name":"Association rule learning","score":0.8156032562255859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8028841614723206},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.7569136619567871},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7476933002471924},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7155546545982361},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6900736093521118},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5361393094062805},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.43872860074043274},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43086397647857666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39489784836769104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35481810569763184},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.19187277555465698}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.8156032562255859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8028841614723206},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.7569136619567871},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7476933002471924},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7155546545982361},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6900736093521118},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5361393094062805},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.43872860074043274},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43086397647857666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39489784836769104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35481810569763184},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.19187277555465698},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3105971.3108450","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3105971.3108450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Symposium on Visual Information Communication and Interaction","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2044289071","https://openalex.org/W2064853889","https://openalex.org/W2170807209","https://openalex.org/W2755087487","https://openalex.org/W2963038743","https://openalex.org/W4252403066"],"related_works":["https://openalex.org/W2390051172","https://openalex.org/W2297208791","https://openalex.org/W2367209111","https://openalex.org/W2351000793","https://openalex.org/W2366790077","https://openalex.org/W2348276166","https://openalex.org/W3034345083","https://openalex.org/W2607264580","https://openalex.org/W3012205960","https://openalex.org/W1483188779"],"abstract_inverted_index":{"Apriori":[0],"Association":[1],"Rule":[2],"Mining":[3],"(ARM)":[4],"is":[5,60,77,95,129],"a":[6,21,32,102,110],"popular":[7],"data":[8,93,105],"mining":[9],"technique":[10],"for":[11,98],"deriving":[12],"association":[13,120],"rules":[14,121,152],"from":[15,31],"frequent":[16,46],"itemsets,":[17],"and":[18,83,137],"it":[19],"has":[20,109],"long":[22],"history.":[23],"Despite":[24],"of":[25,70,104,113,145],"its":[26,28],"popularity,":[27],"performance":[29],"suffers":[30],"bottleneck":[33],"in":[34,40,68],"scalability.":[35],"Many":[36],"attempts":[37],"were":[38],"made":[39],"the":[41,45,66,72,85,90,143],"past,":[42],"including":[43],"changing":[44],"item":[47],"database":[48,67],"structure":[49],"to":[50],"sophisticated":[51],"parallel":[52],"execution.":[53],"In":[54],"this":[55,146],"paper":[56],"an":[57],"alternative":[58],"strategy":[59],"proposed":[61,126],"which":[62,81,107],"centred":[63],"on":[64],"segmenting":[65],"lieu":[69],"using":[71,131],"full":[73],"database.":[74],"The":[75,125,140],"segmentation":[76],"by":[78],"ensemble":[79],"method":[80],"sifts":[82],"selects":[84],"most":[86],"effective":[87],"clustering":[88],"algorithm;":[89],"resultant":[91],"segmented":[92],"cluster":[94],"subsequently":[96],"used":[97],"ARM.":[99],"Using":[100],"only":[101],"fraction":[103],"transactions":[106],"supposedly":[108],"high":[111],"concentration":[112],"expressive":[114],"data,":[115],"ARM":[116,127],"produces":[117],"higher":[118,150],"quality":[119,151],"at":[122],"shorter":[123],"time.":[124],"model":[128,148],"tested":[130],"three":[132],"cases":[133],"-":[134,149],"bank,":[135],"homicide":[136],"lung":[138],"cancer.":[139],"results":[141],"confirm":[142],"usefulness":[144],"new":[147],"are":[153],"gained":[154]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
