{"id":"https://openalex.org/W3115198137","doi":"https://doi.org/10.4018/ijal.2021010102","title":"Efficient Implementations for UWEP Incremental Frequent Itemset Mining Algorithm","display_name":"Efficient Implementations for UWEP Incremental Frequent Itemset Mining Algorithm","publication_year":2020,"publication_date":"2020-12-28","ids":{"openalex":"https://openalex.org/W3115198137","doi":"https://doi.org/10.4018/ijal.2021010102","mag":"3115198137"},"language":"en","primary_location":{"id":"doi:10.4018/ijal.2021010102","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijal.2021010102","pdf_url":null,"source":{"id":"https://openalex.org/S28477642","display_name":"International Journal of Applied Logistics","issn_l":"1947-9573","issn":["1947-9573","1947-9581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Applied Logistics","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/A5061278630","display_name":"Mehmet Bi\u00e7er","orcid":"https://orcid.org/0000-0001-8699-8892"},"institutions":[{"id":"https://openalex.org/I121847817","display_name":"The Graduate Center, CUNY","ror":"https://ror.org/00awd9g61","country_code":"US","type":"education","lineage":["https://openalex.org/I121847817"]},{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mehmet Bicer","raw_affiliation_strings":["Graduate Center, City University of New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Center, City University of New York, USA","institution_ids":["https://openalex.org/I174216632","https://openalex.org/I121847817"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021149156","display_name":"Daniel Indictor","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Indictor","raw_affiliation_strings":["Columbia University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007480648","display_name":"Ryan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan Yang","raw_affiliation_strings":["Massachusetts Institute of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362531","display_name":"Xiaowen Zhang","orcid":"https://orcid.org/0000-0003-3825-6995"},"institutions":[{"id":"https://openalex.org/I142393192","display_name":"College of Staten Island","ror":"https://ror.org/02p179j44","country_code":"US","type":"education","lineage":["https://openalex.org/I142393192"]},{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaowen Zhang","raw_affiliation_strings":["College of Staten Island, City University of New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Staten Island, City University of New York, USA","institution_ids":["https://openalex.org/I142393192","https://openalex.org/I174216632"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1139,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.85242198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"11","issue":"1","first_page":"18","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9236000180244446,"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/association-rule-learning","display_name":"Association rule learning","score":0.862006664276123},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.8484828472137451},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8063367009162903},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7039071321487427},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6297010183334351},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5517544150352478},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.5477095246315002},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4878716468811035},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3380380868911743}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.862006664276123},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.8484828472137451},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8063367009162903},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7039071321487427},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6297010183334351},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5517544150352478},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.5477095246315002},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4878716468811035},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3380380868911743},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijal.2021010102","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijal.2021010102","pdf_url":null,"source":{"id":"https://openalex.org/S28477642","display_name":"International Journal of Applied Logistics","issn_l":"1947-9573","issn":["1947-9573","1947-9581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Applied Logistics","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jal000:v:11:y:2021:i:1:p:18-37","is_oa":false,"landing_page_url":"http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAL.2021010102","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"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":{"Association":[0],"rule":[1],"mining":[2],"is":[3,54,62,79,99,114],"a":[4],"common":[5],"technique":[6],"used":[7],"in":[8,13,16,110,141],"discovering":[9],"interesting":[10],"frequent":[11,41],"patterns":[12,42],"data":[14,30,37],"acquired":[15],"various":[17],"application":[18],"domains.":[19],"The":[20],"search":[21],"space":[22],"combinatorically":[23],"explodes":[24],"as":[25,121],"the":[26,29,33,50,72,90,106,124,137,149,160],"size":[27],"of":[28,35,77,151,159],"increases.":[31],"Furthermore,":[32],"introduction":[34],"new":[36,45,131],"can":[38],"invalidate":[39],"old":[40],"and":[43,59,134,153],"introduce":[44],"ones.":[46],"Hence,":[47],"while":[48],"finding":[49],"association":[51,73,92],"rules":[52,74],"efficiently":[53],"an":[55,118,142],"important":[56],"problem,":[57],"maintaining":[58],"updating":[60],"them":[61,78],"also":[63,83,129],"crucial.":[64],"Several":[65],"algorithms":[66,84],"have":[67],"been":[68],"introduced":[69],"to":[70,86,116,123,136,156],"find":[71],"efficiently.":[75],"One":[76],"Apriori.":[80],"There":[81],"are":[82],"written":[85],"update":[87],"or":[88],"maintain":[89],"existing":[91],"rules.":[93],"Update":[94],"with":[95],"early":[96],"pruning":[97],"(UWEP)":[98],"one":[100],"such":[101],"algorithm.":[102,127],"In":[103],"this":[104],"paper,":[105],"authors":[107],"propose":[108,130],"that":[109],"certain":[111],"conditions":[112],"it":[113],"preferable":[115],"use":[117,150],"incremental":[119],"algorithm":[120,143],"opposed":[122],"classic":[125],"Apriori":[126],"They":[128],"implementation":[132],"techniques":[133],"improvements":[135],"original":[138],"UWEP":[139],"paper":[140],"we":[144],"call":[145],"UWEP2.":[146],"These":[147],"include":[148],"memorization":[152],"lazy":[154],"evaluation":[155],"reduce":[157],"scans":[158],"dataset.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
