{"id":"https://openalex.org/W2079931838","doi":"https://doi.org/10.1109/bigdata.2013.6691742","title":"Frequent Itemset Mining for Big Data","display_name":"Frequent Itemset Mining for Big Data","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W2079931838","doi":"https://doi.org/10.1109/bigdata.2013.6691742","mag":"2079931838"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2013.6691742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2013.6691742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Big Data","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/A5026695911","display_name":"Sandy Moens","orcid":"https://orcid.org/0000-0002-7046-3022"},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Sandy Moens","raw_affiliation_strings":["Universiteit Antwerpen, Belgium","Univ. Antwerpen, Antwerp, Belgium"],"affiliations":[{"raw_affiliation_string":"Universiteit Antwerpen, Belgium","institution_ids":["https://openalex.org/I149213910"]},{"raw_affiliation_string":"Univ. Antwerpen, Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074775047","display_name":"Emin Aksehirli","orcid":null},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Emin Aksehirli","raw_affiliation_strings":["Universiteit Antwerpen, Belgium","Univ. Antwerpen, Antwerp, Belgium"],"affiliations":[{"raw_affiliation_string":"Universiteit Antwerpen, Belgium","institution_ids":["https://openalex.org/I149213910"]},{"raw_affiliation_string":"Univ. Antwerpen, Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020321444","display_name":"Bart Goethals","orcid":"https://orcid.org/0000-0001-9327-9554"},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Bart Goethals","raw_affiliation_strings":["Universiteit Antwerpen, Belgium","Univ. Antwerpen, Antwerp, Belgium"],"affiliations":[{"raw_affiliation_string":"Universiteit Antwerpen, Belgium","institution_ids":["https://openalex.org/I149213910"]},{"raw_affiliation_string":"Univ. Antwerpen, Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026695911"],"corresponding_institution_ids":["https://openalex.org/I149213910"],"apc_list":null,"apc_paid":null,"fwci":50.7787,"has_fulltext":false,"cited_by_count":213,"citation_normalized_percentile":{"value":0.99830427,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"118"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9944000244140625,"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":0.9851999878883362,"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/computer-science","display_name":"Computer science","score":0.825896143913269},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.8232731819152832},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6727227568626404},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6322082877159119},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.590087354183197},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3397548794746399},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.22348430752754211}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.825896143913269},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8232731819152832},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6727227568626404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6322082877159119},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.590087354183197},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3397548794746399},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22348430752754211},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2013.6691742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2013.6691742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Big Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W24211556","https://openalex.org/W132503990","https://openalex.org/W1506285740","https://openalex.org/W1544139368","https://openalex.org/W1597161471","https://openalex.org/W1824634186","https://openalex.org/W1976860187","https://openalex.org/W1995797177","https://openalex.org/W2001782903","https://openalex.org/W2004748427","https://openalex.org/W2025122101","https://openalex.org/W2056910091","https://openalex.org/W2064853889","https://openalex.org/W2076726698","https://openalex.org/W2076743544","https://openalex.org/W2078663894","https://openalex.org/W2080632942","https://openalex.org/W2093456341","https://openalex.org/W2098682382","https://openalex.org/W2105768086","https://openalex.org/W2122465391","https://openalex.org/W2129714679","https://openalex.org/W2133378824","https://openalex.org/W2141115288","https://openalex.org/W2151424115","https://openalex.org/W2161022402","https://openalex.org/W2188584315","https://openalex.org/W2542364126","https://openalex.org/W4231069483","https://openalex.org/W4231087933","https://openalex.org/W4241634004","https://openalex.org/W4252403066","https://openalex.org/W4254918237","https://openalex.org/W6630198464","https://openalex.org/W6635733350","https://openalex.org/W6729140741"],"related_works":["https://openalex.org/W4322629366","https://openalex.org/W2808989540","https://openalex.org/W2397053934","https://openalex.org/W1039292361","https://openalex.org/W2551093110","https://openalex.org/W2148016376","https://openalex.org/W4237919137","https://openalex.org/W3184179822","https://openalex.org/W3095362084","https://openalex.org/W3003361536"],"abstract_inverted_index":{"Frequent":[0],"Itemset":[1],"Mining":[2],"(FIM)":[3],"is":[4,96],"one":[5],"of":[6,20,40,74,111],"the":[7,38,72,78,109],"most":[8],"well":[9],"known":[10],"techniques":[11,76],"to":[12,31,47,98],"extract":[13],"knowledge":[14],"from":[15],"data.":[16],"The":[17],"combinatorial":[18],"explosion":[19],"FIM":[21,75],"methods":[22,85],"become":[23],"even":[24],"more":[25],"problematic":[26],"when":[27],"they":[28],"are":[29],"applied":[30],"Big":[32],"Data.":[33],"Fortunately,":[34],"recent":[35],"improvements":[36],"in":[37],"field":[39],"parallel":[41],"programming":[42],"already":[43],"provide":[44],"good":[45],"tools":[46,53],"tackle":[48],"this":[49,68],"problem.":[50],"However,":[51],"these":[52],"come":[54],"with":[55],"their":[56],"own":[57],"technical":[58],"challenges,":[59],"e.g.":[60],"balanced":[61],"data":[62],"distribution":[63],"and":[64],"inter-communication":[65],"costs.":[66],"In":[67,104],"paper,":[69],"we":[70,107],"investigate":[71],"applicability":[73],"on":[77,92,100],"MapReduce":[79],"platform.":[80],"We":[81],"introduce":[82],"two":[83],"new":[84],"for":[86],"mining":[87],"large":[88,102],"datasets:":[89],"Dist-Eclat":[90],"focuses":[91],"speed":[93],"while":[94],"BigFIM":[95],"optimized":[97],"run":[99],"really":[101],"datasets.":[103],"our":[105,112],"experiments":[106],"show":[108],"scalability":[110],"methods.":[113]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":27},{"year":2018,"cited_by_count":31},{"year":2017,"cited_by_count":31},{"year":2016,"cited_by_count":30},{"year":2015,"cited_by_count":22},{"year":2014,"cited_by_count":8}],"updated_date":"2026-03-28T06:11:35.319607","created_date":"2025-10-10T00:00:00"}
