{"id":"https://openalex.org/W2065998343","doi":"https://doi.org/10.2478/s13537-011-0016-y","title":"Analysis of the progressive sampling-based approach using real life datasets","display_name":"Analysis of the progressive sampling-based approach using real life datasets","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W2065998343","doi":"https://doi.org/10.2478/s13537-011-0016-y","mag":"2065998343"},"language":"en","primary_location":{"id":"doi:10.2478/s13537-011-0016-y","is_oa":true,"landing_page_url":"https://doi.org/10.2478/s13537-011-0016-y","pdf_url":"https://www.degruyter.com/document/doi/10.2478/s13537-011-0016-y/pdf","source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.degruyter.com/document/doi/10.2478/s13537-011-0016-y/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103498659","display_name":"Venkatapathy Umarani","orcid":null},"institutions":[{"id":"https://openalex.org/I4400600945","display_name":"Anna University Regional Campus, Coimbatore","ror":"https://ror.org/057qyqy03","country_code":null,"type":"education","lineage":["https://openalex.org/I4400600945"]},{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Venkatapathy Umarani","raw_affiliation_strings":["Anna University, Coimbatore, India","Anna University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anna University, Coimbatore, India","institution_ids":["https://openalex.org/I4400600945","https://openalex.org/I33585257"]},{"raw_affiliation_string":"Anna University","institution_ids":["https://openalex.org/I33585257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021135928","display_name":"M. Punithavalli","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136184","display_name":"Studief\u00f6rbundet N\u00e4ringsliv och Samh\u00e4lle","ror":"https://ror.org/04dxwt824","country_code":"SE","type":"education","lineage":["https://openalex.org/I4210136184"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Muthusamy Punithavalli","raw_affiliation_strings":["Department of Computer Applications, SNS College of Engineering, Coimbatore, India","SNS College of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Applications, SNS College of Engineering, Coimbatore, India","institution_ids":[]},{"raw_affiliation_string":"SNS College of Engineering","institution_ids":["https://openalex.org/I4210136184"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103498659"],"corresponding_institution_ids":["https://openalex.org/I33585257","https://openalex.org/I4400600945"],"apc_list":{"value":1000,"currency":"EUR","value_usd":1078},"apc_paid":{"value":1000,"currency":"EUR","value_usd":1078},"fwci":0.0,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.1568741,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"1","issue":"2","first_page":null,"last_page":null},"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":0.9646000266075134,"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":0.9467999935150146,"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":0.9353278875350952},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.8071526885032654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7321783304214478},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6636799573898315},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.6541848182678223},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6243364810943604},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5507925748825073},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.546139657497406},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.48109978437423706},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.47825777530670166},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.45795735716819763},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43335655331611633},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35690534114837646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32529574632644653},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18520087003707886},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09060809016227722}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.9353278875350952},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.8071526885032654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7321783304214478},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6636799573898315},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.6541848182678223},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6243364810943604},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5507925748825073},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.546139657497406},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.48109978437423706},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.47825777530670166},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.45795735716819763},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43335655331611633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35690534114837646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32529574632644653},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18520087003707886},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09060809016227722},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2478/s13537-011-0016-y","is_oa":true,"landing_page_url":"https://doi.org/10.2478/s13537-011-0016-y","pdf_url":"https://www.degruyter.com/document/doi/10.2478/s13537-011-0016-y/pdf","source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6b2948fd0b054b79b759c6c114b5abc6","is_oa":true,"landing_page_url":"https://doaj.org/article/6b2948fd0b054b79b759c6c114b5abc6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Open Computer Science, Vol 1, Iss 2, Pp 221-242 (2011)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.2478/s13537-011-0016-y","is_oa":true,"landing_page_url":"https://doi.org/10.2478/s13537-011-0016-y","pdf_url":"https://www.degruyter.com/document/doi/10.2478/s13537-011-0016-y/pdf","source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","score":0.4099999964237213,"display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2065998343.pdf","grobid_xml":"https://content.openalex.org/works/W2065998343.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W39877551","https://openalex.org/W202330906","https://openalex.org/W208128215","https://openalex.org/W1025324079","https://openalex.org/W1481444010","https://openalex.org/W1484413656","https://openalex.org/W1486039312","https://openalex.org/W1510681818","https://openalex.org/W1516812818","https://openalex.org/W1524454721","https://openalex.org/W1560141943","https://openalex.org/W1562805786","https://openalex.org/W1591002430","https://openalex.org/W1598051036","https://openalex.org/W1965392447","https://openalex.org/W1994326354","https://openalex.org/W2003870406","https://openalex.org/W2020611145","https://openalex.org/W2028944004","https://openalex.org/W2032387160","https://openalex.org/W2045487373","https://openalex.org/W2062277303","https://openalex.org/W2070802104","https://openalex.org/W2074410497","https://openalex.org/W2104731482","https://openalex.org/W2126310301","https://openalex.org/W2131962337","https://openalex.org/W2139655910","https://openalex.org/W2140190241","https://openalex.org/W2143477272","https://openalex.org/W2158242568","https://openalex.org/W2166268523","https://openalex.org/W2166559705","https://openalex.org/W2172249200","https://openalex.org/W2185756862","https://openalex.org/W2311675417","https://openalex.org/W2334510206","https://openalex.org/W2537030075","https://openalex.org/W2585105539","https://openalex.org/W2998574808","https://openalex.org/W4212848460","https://openalex.org/W4247210760"],"related_works":["https://openalex.org/W2390051172","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","https://openalex.org/W2383378197"],"abstract_inverted_index":{"Abstract":[0],"The":[1,172],"discovery":[2],"of":[3,15,48,68,144,159,181,191],"association":[4,21,49,69,81,129,167,192],"rules":[5,22,82,130,193],"is":[6,34,52,77,101,125,162,186],"an":[7,93,141],"important":[8],"and":[9,30,96,178],"challenging":[10],"data":[11],"mining":[12,51,80,169,190],"task.":[13],"Most":[14],"the":[16,27,46,66,98,104,110,114,118,122,145,157,160,165,182,195],"existing":[17],"algorithms":[18],"for":[19,37,63,79,113],"finding":[20],"require":[23],"multiple":[24],"passes":[25],"over":[26],"entire":[28],"database,":[29],"I/O":[31],"overhead":[32],"incurred":[33],"extremely":[35],"high":[36],"very":[38],"large":[39,84],"databases.":[40,85],"An":[41],"obvious":[42],"approach":[43,76,148,161,185],"to":[44],"reduce":[45],"complexity":[47],"rule":[50,70,168],"sampling.":[53],"In":[54,135],"recent":[55],"times,":[56],"several":[57],"sampling-based":[58,75,147,184],"approaches":[59],"have":[60,139],"been":[61],"developed":[62],"speeding":[64],"up":[65],"process":[67],"mining.":[71],"A":[72],"proficient":[73],"progressive":[74,146,183],"presented":[78,140],"from":[83,92,103,133,194],"At":[86],"first,":[87],"frequent":[88,106],"itemsets":[89],"are":[90,131],"mined":[91,105,132],"initial":[94],"sample":[95,123],"subsequently,":[97],"negative":[99,120],"border":[100],"computed":[102,112],"itemsets.":[107],"Based":[108],"on":[109],"support":[111],"midpoint":[115],"itemset":[116],"in":[117,155,189],"sorted":[119],"border,":[121],"size":[124],"either":[126],"increased":[127],"or":[128],"it.":[134],"this":[136],"paper,":[137],"we":[138],"extensive":[142],"analysis":[143],"with":[149,164],"different":[150],"real":[151,196],"life":[152,197],"datasets":[153],"and,":[154],"addition,":[156],"performance":[158],"evaluated":[163],"well-known":[166],"algorithm,":[170],"Apriori.":[171],"experimental":[173],"results":[174],"show":[175],"that":[176],"accuracy":[177],"computation":[179],"time":[180],"effectively":[187],"improved":[188],"datasets.":[198]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2016-06-24T00:00:00"}