{"id":"https://openalex.org/W1605878449","doi":"https://doi.org/10.1109/icmla.2004.1383532","title":"A comparative study among three algorithms for frequent pattern generation","display_name":"A comparative study among three algorithms for frequent pattern generation","publication_year":2005,"publication_date":"2005-04-06","ids":{"openalex":"https://openalex.org/W1605878449","doi":"https://doi.org/10.1109/icmla.2004.1383532","mag":"1605878449"},"language":"en","primary_location":{"id":"doi:10.1109/icmla.2004.1383532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2004.1383532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Machine Learning and Applications, 2004. Proceedings.","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/A5101977437","display_name":"Rakibul M. Islam","orcid":"https://orcid.org/0000-0002-0889-8658"},"institutions":[{"id":"https://openalex.org/I205746353","display_name":"University of Dhaka","ror":"https://ror.org/05wv2vq37","country_code":"BD","type":"education","lineage":["https://openalex.org/I205746353"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"R. Islam","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Dhaka, Bangladesh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Dhaka, Bangladesh","institution_ids":["https://openalex.org/I205746353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101863352","display_name":"Salman Khan","orcid":"https://orcid.org/0000-0002-3294-7173"},"institutions":[{"id":"https://openalex.org/I205746353","display_name":"University of Dhaka","ror":"https://ror.org/05wv2vq37","country_code":"BD","type":"education","lineage":["https://openalex.org/I205746353"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"S.M. Khan","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Dhaka, Bangladesh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Dhaka, Bangladesh","institution_ids":["https://openalex.org/I205746353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055951031","display_name":"Majid Zaman","orcid":"https://orcid.org/0000-0003-1070-8195"},"institutions":[{"id":"https://openalex.org/I205746353","display_name":"University of Dhaka","ror":"https://ror.org/05wv2vq37","country_code":"BD","type":"education","lineage":["https://openalex.org/I205746353"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"M. Azud us zaman","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Dhaka, Bangladesh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Dhaka, Bangladesh","institution_ids":["https://openalex.org/I205746353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084342000","display_name":"S.S. Kabir Robin","orcid":null},"institutions":[{"id":"https://openalex.org/I205746353","display_name":"University of Dhaka","ror":"https://ror.org/05wv2vq37","country_code":"BD","type":"education","lineage":["https://openalex.org/I205746353"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"S.S. Kabir Robin","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Dhaka, Bangladesh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Dhaka, Bangladesh","institution_ids":["https://openalex.org/I205746353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205746353"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09595686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"52","issue":null,"first_page":"336","last_page":"343"},"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":0.993399977684021,"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":0.9850999712944031,"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/computer-science","display_name":"Computer science","score":0.7685466408729553},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7393897175788879},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.6775141954421997},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.6600835919380188},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6465637683868408},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.629021406173706},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5410721302032471},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5170758366584778},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.49776914715766907},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.44566667079925537},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4384627938270569},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3374154567718506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2647465169429779},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11007508635520935},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08605465292930603}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7685466408729553},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7393897175788879},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.6775141954421997},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.6600835919380188},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6465637683868408},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.629021406173706},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5410721302032471},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5170758366584778},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.49776914715766907},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.44566667079925537},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4384627938270569},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3374154567718506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2647465169429779},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11007508635520935},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08605465292930603},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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:10.1109/icmla.2004.1383532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2004.1383532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Machine Learning and Applications, 2004. Proceedings.","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":16,"referenced_works":["https://openalex.org/W110175884","https://openalex.org/W1482472192","https://openalex.org/W1483679765","https://openalex.org/W1484413656","https://openalex.org/W1506285740","https://openalex.org/W2030969394","https://openalex.org/W2037965136","https://openalex.org/W2064853889","https://openalex.org/W2141115288","https://openalex.org/W2752198569","https://openalex.org/W4250256819","https://openalex.org/W4252403066","https://openalex.org/W6628750762","https://openalex.org/W6628970668","https://openalex.org/W6628973722","https://openalex.org/W6658211355"],"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":{"Efficient":[0],"algorithms":[1,121],"to":[2,8,28,55,80,107],"mine":[3,81],"frequent":[4,50,83,118],"patterns":[5,84],"are":[6,122,126],"crucial":[7],"many":[9,44],"tasks":[10],"in":[11,20,85],"data":[12],"mining.":[13],"Since":[14],"the":[15,68,71,92,131,176],"Apriori":[16,139],"algorithm":[17,63,90,133],"was":[18],"proposed":[19,27],"1994,":[21],"there":[22],"have":[23],"been":[24],"several":[25],"methods":[26,45],"improve":[29],"its":[30,36],"performance.":[31],"However,":[32],"most":[33],"still":[34],"adopt":[35],"candidate":[37,96],"set":[38,97],"generationand-":[39],"test":[40],"approach.":[41],"In":[42,113],"addition,":[43],"do":[46],"not":[47],"generate":[48],"all":[49,82],"patterns,":[51],"making":[52],"them":[53],"inadequate":[54],"derive":[56],"association":[57],"rules.":[58],"The":[59],"Pattern":[60],"Decomposition":[61],"(PD)":[62],"that":[64,130],"can":[65],"significantly":[66],"reduce":[67],"size":[69],"of":[70,95,104,138,143,152],"dataset":[72],"on":[73],"each":[74],"pass":[75],"makes":[76],"it":[77],"more":[78,173],"efficient":[79],"a":[86,101],"large":[87],"dataset.":[88],"This":[89],"avoids":[91],"costly":[93],"process":[94],"generation":[98,120],"and":[99,154,178],"saves":[100],"great":[102],"amount":[103],"counting":[105],"time":[106],"evaluate":[108],"support":[109],"with":[110],"reduced":[111],"datasets.":[112],"this":[114],"paper,":[115],"some":[116],"existing":[117],"pattern":[119],"explored,":[123],"their":[124],"comparisons":[125],"discussed,":[127],"which":[128],"shows":[129],"PD":[132,170],"outperforms":[134],"an":[135,158],"improved":[136,159],"version":[137],"named":[140,163],"Direct":[141],"Count":[142],"candidates":[144],"&":[145],"Prune":[146],"transactions":[147],"(DCP)":[148],"by":[149],"one":[150],"order":[151],"magnitude":[153],"is":[155,171],"faster":[156],"than":[157,175],"FP-tree":[160],"(Frequent":[161],"Pattern)":[162],"as":[164],"Predictive":[165],"Item":[166],"Pruning":[167],"(PIP).":[168],"Further,":[169],"also":[172],"scalable":[174],"DCP":[177],"PIP.":[179]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}