{"id":"https://openalex.org/W1512128658","doi":"https://doi.org/10.1109/retis.2015.7232867","title":"Discovering association rules partially devoid of dissociation by weighted confidence","display_name":"Discovering association rules partially devoid of dissociation by weighted confidence","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1512128658","doi":"https://doi.org/10.1109/retis.2015.7232867","mag":"1512128658"},"language":"en","primary_location":{"id":"doi:10.1109/retis.2015.7232867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/retis.2015.7232867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS)","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/A5037158319","display_name":"Subrata Datta","orcid":"https://orcid.org/0000-0002-5910-8273"},"institutions":[{"id":"https://openalex.org/I4210145362","display_name":"Institute of Technology Management","ror":"https://ror.org/03c4qaa56","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1340206300","https://openalex.org/I4210145362","https://openalex.org/I4210150591"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subrata Datta","raw_affiliation_strings":["Department of Information Technology, Neotia Institute of Technology, Kolkata, India","Department of Information Technology, Neotia Institute of Technology, Management & Science, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Neotia Institute of Technology, Kolkata, India","institution_ids":[]},{"raw_affiliation_string":"Department of Information Technology, Neotia Institute of Technology, Management & Science, Kolkata, India","institution_ids":["https://openalex.org/I4210145362"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038988792","display_name":"Subrata Bose","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145362","display_name":"Institute of Technology Management","ror":"https://ror.org/03c4qaa56","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1340206300","https://openalex.org/I4210145362","https://openalex.org/I4210150591"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subrata Bose","raw_affiliation_strings":["Department of Information Technology, Neotia Institute of Technology, Kolkata, India","Department of Computer Science & Engineering, Neotia Institute of Technology, Management & Science, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Neotia Institute of Technology, Kolkata, India","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science & Engineering, Neotia Institute of Technology, Management & Science, Kolkata, India","institution_ids":["https://openalex.org/I4210145362"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2983,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.92650646,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"138","last_page":"143"},"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":0.9968000054359436,"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":0.9555000066757202,"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":0.8480544090270996},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.620702862739563},{"id":"https://openalex.org/keywords/dissociation","display_name":"Dissociation (chemistry)","score":0.5788664817810059},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.5777313113212585},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5734596252441406},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5423063635826111},{"id":"https://openalex.org/keywords/null","display_name":"Null (SQL)","score":0.5292339324951172},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44698381423950195},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3475393056869507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30542701482772827},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21254852414131165},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.1290038824081421}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.8480544090270996},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.620702862739563},{"id":"https://openalex.org/C102931765","wikidata":"https://www.wikidata.org/wiki/Q189673","display_name":"Dissociation (chemistry)","level":2,"score":0.5788664817810059},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.5777313113212585},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5734596252441406},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5423063635826111},{"id":"https://openalex.org/C203763787","wikidata":"https://www.wikidata.org/wiki/Q371029","display_name":"Null (SQL)","level":2,"score":0.5292339324951172},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44698381423950195},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3475393056869507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30542701482772827},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21254852414131165},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.1290038824081421},{"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/C147789679","wikidata":"https://www.wikidata.org/wiki/Q11372","display_name":"Physical chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/retis.2015.7232867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/retis.2015.7232867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1567446043","https://openalex.org/W1581468894","https://openalex.org/W1815606412","https://openalex.org/W1892399053","https://openalex.org/W1964782720","https://openalex.org/W1972732338","https://openalex.org/W1988606047","https://openalex.org/W2004524589","https://openalex.org/W2026562765","https://openalex.org/W2037965136","https://openalex.org/W2045029544","https://openalex.org/W2048468770","https://openalex.org/W2057858164","https://openalex.org/W2064853889","https://openalex.org/W2083386287","https://openalex.org/W2094770144","https://openalex.org/W2098268836","https://openalex.org/W2113741323","https://openalex.org/W2118615833","https://openalex.org/W2119238968","https://openalex.org/W2126765873","https://openalex.org/W2135333448","https://openalex.org/W2166361526","https://openalex.org/W2166559705","https://openalex.org/W4252403066","https://openalex.org/W4253376897","https://openalex.org/W6634656658","https://openalex.org/W6677034569","https://openalex.org/W6677819563"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W2751920613","https://openalex.org/W2415164632","https://openalex.org/W2113309085","https://openalex.org/W2410549043","https://openalex.org/W3014936414","https://openalex.org/W2394010168","https://openalex.org/W2993700121","https://openalex.org/W2184109998","https://openalex.org/W2362772308"],"abstract_inverted_index":{"Useful":[0],"rule":[1,172],"formation":[2],"from":[3],"frequent":[4,26,150],"itemsets":[5],"in":[6,14,52,62,102,134,155,165,221],"a":[7,11,118],"large":[8],"database":[9],"is":[10,93],"crucial":[12],"task":[13],"Association":[15],"Rule":[16],"mining.":[17],"Traditionally":[18],"association":[19,123],"rules":[20,81,124,136,161,201],"refer":[21],"to":[22,111,121,147,207],"associations":[23,39],"between":[24],"two":[25],"sets":[27,151],"and":[28,40,49,79,82,142,159,181,219],"measured":[29],"by":[30,125,152,162],"their":[31],"confidence.":[32],"This":[33],"approach":[34,120,195],"basically":[35],"concentrates":[36],"on":[37],"positive":[38,78,104,171],"thereby":[41],"do":[42],"not":[43],"study":[44],"the":[45,55,64,85,88,127,135,149,177,190,197,208],"effect":[46,56,128],"of":[47,57,66,87,99,129,132,157,167,176,199,217],"dissociation":[48,58,180],"null":[50,67,89,100],"transactions":[51,68,101,133],"association.":[53],"Though":[54],"has":[59,69],"been":[60,70],"studied":[61,84],"association,":[63],"impact":[65,86],"generally":[71],"ignored.":[72],"Some":[73],"scholars":[74],"have":[75,109,116,145,187],"identified":[76],"both":[77,222],"negative":[80,106],"thus":[83],"transactions.":[90],"However":[91],"there":[92],"no":[94],"uniform":[95,119],"treatment":[96],"towards":[97],"inclusion":[98],"either":[103],"or":[105],"category.":[107],"We":[108,115,144,186],"tried":[110],"bridge":[112],"these":[113],"gaps.":[114],"established":[117],"mine":[122],"combining":[126],"all":[130],"kinds":[131],"without":[137],"categorizing":[138],"them":[139],"as":[140],"positives":[141],"negatives.":[143],"proposed":[146],"identify":[148],"weighted":[153,163,191,193],"support":[154,158],"lieu":[156,166],"measure":[160],"confidence":[164,168,194],"for":[169],"useful":[170],"generation":[173],"taking":[174],"care":[175],"negativity":[178],"through":[179],"Null":[182],"Transaction":[183],"Impact":[184],"Factor.":[185],"shown":[188],"that":[189],"support,":[192],"increases":[196],"chance":[198],"discovering":[200],"which":[202],"are":[203],"less":[204],"dissociated":[205],"compared":[206],"traditional":[209],"support-confidence":[210],"framework":[211],"provided":[212],"we":[213],"maintain":[214],"same":[215],"level":[216],"minsupp":[218],"minconf":[220],"cases.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}