{"id":"https://openalex.org/W3130049154","doi":"https://doi.org/10.23919/fruct50888.2021.9347577","title":"Clustering Based Approach to Enhance Association Rule Mining","display_name":"Clustering Based Approach to Enhance Association Rule Mining","publication_year":2021,"publication_date":"2021-01-27","ids":{"openalex":"https://openalex.org/W3130049154","doi":"https://doi.org/10.23919/fruct50888.2021.9347577","mag":"3130049154"},"language":"en","primary_location":{"id":"doi:10.23919/fruct50888.2021.9347577","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fruct50888.2021.9347577","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 28th Conference of Open Innovations Association (FRUCT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doaj.org/article/1b164e1e90a1487fbc43619ef29c54f1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031444850","display_name":"Samruddhi Kanhere","orcid":null},"institutions":[{"id":"https://openalex.org/I104546213","display_name":"National College of Ireland","ror":"https://ror.org/02qzs9336","country_code":"IE","type":"education","lineage":["https://openalex.org/I104546213"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Samruddhi Kanhere","raw_affiliation_strings":["School Of Computing, National College of Ireland,Dublin,Ireland","School Of Computing, National College of Ireland, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"School Of Computing, National College of Ireland,Dublin,Ireland","institution_ids":["https://openalex.org/I104546213"]},{"raw_affiliation_string":"School Of Computing, National College of Ireland, Dublin, Ireland","institution_ids":["https://openalex.org/I104546213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026192892","display_name":"Anu Sahni","orcid":null},"institutions":[{"id":"https://openalex.org/I104546213","display_name":"National College of Ireland","ror":"https://ror.org/02qzs9336","country_code":"IE","type":"education","lineage":["https://openalex.org/I104546213"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Anu Sahni","raw_affiliation_strings":["School Of Computing, National College of Ireland,Dublin,Ireland","School Of Computing, National College of Ireland, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"School Of Computing, National College of Ireland,Dublin,Ireland","institution_ids":["https://openalex.org/I104546213"]},{"raw_affiliation_string":"School Of Computing, National College of Ireland, Dublin, Ireland","institution_ids":["https://openalex.org/I104546213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005294047","display_name":"Paul Stynes","orcid":"https://orcid.org/0000-0002-4725-5698"},"institutions":[{"id":"https://openalex.org/I104546213","display_name":"National College of Ireland","ror":"https://ror.org/02qzs9336","country_code":"IE","type":"education","lineage":["https://openalex.org/I104546213"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Paul Stynes","raw_affiliation_strings":["School Of Computing, National College of Ireland,Dublin,Ireland","School Of Computing, National College of Ireland, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"School Of Computing, National College of Ireland,Dublin,Ireland","institution_ids":["https://openalex.org/I104546213"]},{"raw_affiliation_string":"School Of Computing, National College of Ireland, Dublin, Ireland","institution_ids":["https://openalex.org/I104546213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037446814","display_name":"Pramod Pathak","orcid":"https://orcid.org/0000-0001-5631-2298"},"institutions":[{"id":"https://openalex.org/I104546213","display_name":"National College of Ireland","ror":"https://ror.org/02qzs9336","country_code":"IE","type":"education","lineage":["https://openalex.org/I104546213"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Pramod Pathak","raw_affiliation_strings":["School Of Computing, National College of Ireland,Dublin,Ireland","School Of Computing, National College of Ireland, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"School Of Computing, National College of Ireland,Dublin,Ireland","institution_ids":["https://openalex.org/I104546213"]},{"raw_affiliation_string":"School Of Computing, National College of Ireland, Dublin, Ireland","institution_ids":["https://openalex.org/I104546213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031444850"],"corresponding_institution_ids":["https://openalex.org/I104546213"],"apc_list":null,"apc_paid":null,"fwci":1.9908,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88537505,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"142","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9980000257492065,"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":0.9980000257492065,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9649999737739563,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9585999846458435,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.8921984434127808},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7495988011360168},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7437729835510254},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7246619462966919},{"id":"https://openalex.org/keywords/affinity-analysis","display_name":"Affinity analysis","score":0.7240446209907532},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.6594310998916626},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5614416599273682},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5538173317909241},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.5388372540473938},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4936915338039398},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4670015573501587},{"id":"https://openalex.org/keywords/differential","display_name":"Differential (mechanical device)","score":0.42021456360816956},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4114561080932617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28168785572052},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21742594242095947},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11126977205276489},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09933215379714966},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09053441882133484}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.8921984434127808},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7495988011360168},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7437729835510254},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7246619462966919},{"id":"https://openalex.org/C23906176","wikidata":"https://www.wikidata.org/wiki/Q727515","display_name":"Affinity analysis","level":3,"score":0.7240446209907532},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.6594310998916626},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5614416599273682},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5538173317909241},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.5388372540473938},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4936915338039398},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4670015573501587},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.42021456360816956},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4114561080932617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28168785572052},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21742594242095947},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11126977205276489},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09933215379714966},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09053441882133484},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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":4,"locations":[{"id":"doi:10.23919/fruct50888.2021.9347577","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fruct50888.2021.9347577","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 28th Conference of Open Innovations Association (FRUCT)","raw_type":"proceedings-article"},{"id":"pmh:oai:norma.ncirl.ie:4403","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400345","display_name":"TRAP@NCI (National College of Ireland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I104546213","host_organization_name":"National College of Ireland","host_organization_lineage":["https://openalex.org/I104546213"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},{"id":"pmh:oai:doaj.org/article:1b164e1e90a1487fbc43619ef29c54f1","is_oa":true,"landing_page_url":"https://doaj.org/article/1b164e1e90a1487fbc43619ef29c54f1","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 28, Iss 1, Pp 142-150 (2021)","raw_type":"article"},{"id":"pmh:oai:norma.ncirl.ie:4902","is_oa":false,"landing_page_url":"http://norma.ncirl.ie/4902/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400345","display_name":"TRAP@NCI (National College of Ireland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I104546213","host_organization_name":"National College of Ireland","host_organization_lineage":["https://openalex.org/I104546213"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Book Section"}],"best_oa_location":{"id":"pmh:oai:doaj.org/article:1b164e1e90a1487fbc43619ef29c54f1","is_oa":true,"landing_page_url":"https://doaj.org/article/1b164e1e90a1487fbc43619ef29c54f1","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 28, Iss 1, Pp 142-150 (2021)","raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1974096261","https://openalex.org/W2003772366","https://openalex.org/W2011478918","https://openalex.org/W2080632942","https://openalex.org/W2166559705","https://openalex.org/W2589682190","https://openalex.org/W2668848100","https://openalex.org/W2750024164","https://openalex.org/W2765086547","https://openalex.org/W2773681603","https://openalex.org/W2780247929","https://openalex.org/W2792092058","https://openalex.org/W2892778755","https://openalex.org/W2920999084","https://openalex.org/W2968893289","https://openalex.org/W2977976803","https://openalex.org/W3011086883","https://openalex.org/W3034801954","https://openalex.org/W3042114369","https://openalex.org/W4231069483","https://openalex.org/W4236240245"],"related_works":["https://openalex.org/W2607264580","https://openalex.org/W2587896742","https://openalex.org/W4284697452","https://openalex.org/W1997795943","https://openalex.org/W4308793916","https://openalex.org/W3119453588","https://openalex.org/W1998540199","https://openalex.org/W1481792368","https://openalex.org/W3036124657","https://openalex.org/W4248176152"],"abstract_inverted_index":{"Association":[0],"rule":[1],"mining":[2],"algorithms":[3,27],"such":[4],"as":[5,52],"Apriori":[6],"and":[7,63,130,216],"FPGrowth":[8],"are":[9,57,87],"extensively":[10],"being":[11],"used":[12,162],"in":[13,90,121,163],"the":[14,23,31,36,49,91,103,116,127,133,154,178,190,209],"retail":[15],"industry":[16],"to":[17,28,72,82,125,177,188,201],"uncover":[18],"consumer":[19],"buying":[20],"patterns.":[21],"However,":[22],"scalability":[24],"of":[25,68,106,115,157,169],"these":[26],"deal":[29],"with":[30],"voraciously":[32],"increasing":[33],"data":[34],"is":[35,71,100,196],"major":[37],"challenge.":[38],"This":[39],"research":[40],"presents":[41],"a":[42,53,96,146],"novel":[43],"Clustering":[44],"based":[45,59],"approach":[46,161],"by":[47,76,111,182,223],"reducing":[48,126,132],"dataset":[50],"size":[51],"solution.":[54],"The":[55],"products":[56],"clustered":[58],"on":[60],"their":[61,175],"frequency":[62],"price.":[64,185],"Another":[65],"important":[66],"aspect":[67],"this":[69,164],"study":[70,165],"find":[73],"interesting":[74,148],"rules":[75,85,107,149,219],"performing":[77],"differential":[78,140,225],"market":[79,141,226],"basket":[80,142,227],"analysis":[81,143],"identify":[83],"association":[84],"which":[86,120,150],"likely":[88],"ignored":[89],"trivial":[92],"approach.":[93],"When":[94],"using":[95,112],"cluster-based":[97],"approach,":[98],"it":[99],"observed":[101],"that":[102,208],"same":[104],"set":[105,156],"can":[108,212,220],"be":[109,213,221],"generated":[110,222],"only":[113,167],"7%":[114],"total":[117],"16210":[118],"items,":[119],"turn":[122],"directly":[123],"contributes":[124],"processing":[128],"overheads":[129],"thus":[131],"computation":[134,210],"time.":[135],"Furthermore,":[136],"results":[137,205],"obtained":[138],"from":[139,153,199],"have":[144],"highlighted":[145],"few":[147],"were":[151],"missing":[152],"original":[155],"rules.":[158],"A":[159],"clustering-based":[160],"not":[166],"consists":[168],"frequent":[170],"items":[171],"but":[172],"also":[173,197],"considers":[174],"contribution":[176],"overall":[179],"revenue":[180],"generation":[181],"considering":[183],"its":[184],"In":[186],"addition":[187],"this,":[189],"least":[191],"contributing":[192],"product":[193],"exclusion":[194],"rate":[195],"improved":[198],"45%":[200],"93":[202],"%.":[203],"These":[204],"evidently":[206],"suggest":[207],"cost":[211],"significantly":[214],"reduced,":[215],"more":[217],"accurate":[218],"applying":[224],"analysis.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
