{"id":"https://openalex.org/W3007811135","doi":"https://doi.org/10.1109/bigdata47090.2019.9006305","title":"Enhancing Itemset Tree Rules and Performance","display_name":"Enhancing Itemset Tree Rules and Performance","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007811135","doi":"https://doi.org/10.1109/bigdata47090.2019.9006305","mag":"3007811135"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (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/A5080983983","display_name":"Jay B. Lewis","orcid":null},"institutions":[{"id":"https://openalex.org/I83809506","display_name":"University of South Alabama","ror":"https://ror.org/01s7b5y08","country_code":"US","type":"education","lineage":["https://openalex.org/I83809506"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jay Lewis","raw_affiliation_strings":["Computer Science, School of Computing, University of South Alabama, Mobile, Alabama, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science, School of Computing, University of South Alabama, Mobile, Alabama, USA","institution_ids":["https://openalex.org/I83809506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005864826","display_name":"Ryan Benton","orcid":"https://orcid.org/0000-0001-9616-6221"},"institutions":[{"id":"https://openalex.org/I83809506","display_name":"University of South Alabama","ror":"https://ror.org/01s7b5y08","country_code":"US","type":"education","lineage":["https://openalex.org/I83809506"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan G. Benton","raw_affiliation_strings":["Computer Science, School of Computing, University of South Alabama, Mobile, Alabama, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science, School of Computing, University of South Alabama, Mobile, Alabama, USA","institution_ids":["https://openalex.org/I83809506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023672178","display_name":"David Bourrie","orcid":"https://orcid.org/0000-0002-5009-6843"},"institutions":[{"id":"https://openalex.org/I83809506","display_name":"University of South Alabama","ror":"https://ror.org/01s7b5y08","country_code":"US","type":"education","lineage":["https://openalex.org/I83809506"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Bourrie","raw_affiliation_strings":["Information Systems and Technology, School of Computing, University of South Alabama, Mobile, Alabama, USA"],"affiliations":[{"raw_affiliation_string":"Information Systems and Technology, School of Computing, University of South Alabama, Mobile, Alabama, USA","institution_ids":["https://openalex.org/I83809506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022383594","display_name":"Jennifer Lavergne","orcid":null},"institutions":[{"id":"https://openalex.org/I172951950","display_name":"McNeese State University","ror":"https://ror.org/00h04da97","country_code":"US","type":"education","lineage":["https://openalex.org/I172951950","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Lavergne","raw_affiliation_strings":["Electrical Engineering and Computer Science, McNeese State University, Lake Charles, Louisiana, USA"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, McNeese State University, Lake Charles, Louisiana, USA","institution_ids":["https://openalex.org/I172951950"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5080983983"],"corresponding_institution_ids":["https://openalex.org/I83809506"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.30653621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1143","last_page":"1150"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.9879000186920166,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7413756847381592},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5313138365745544},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08540499210357666}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7413756847381592},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5313138365745544},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08540499210357666},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W137694392","https://openalex.org/W138971572","https://openalex.org/W314658084","https://openalex.org/W981854434","https://openalex.org/W1506285740","https://openalex.org/W1509287603","https://openalex.org/W1534296789","https://openalex.org/W1819040843","https://openalex.org/W1951217842","https://openalex.org/W1965728860","https://openalex.org/W1977055639","https://openalex.org/W2016661940","https://openalex.org/W2032226242","https://openalex.org/W2033769446","https://openalex.org/W2064853889","https://openalex.org/W2093421556","https://openalex.org/W2101056238","https://openalex.org/W2112104703","https://openalex.org/W2115482638","https://openalex.org/W2125231721","https://openalex.org/W2144583862","https://openalex.org/W2161591307","https://openalex.org/W2166559705","https://openalex.org/W2507635762","https://openalex.org/W3120740533","https://openalex.org/W6605550097","https://openalex.org/W6605595290","https://openalex.org/W6630198464","https://openalex.org/W6630363918","https://openalex.org/W6632033116","https://openalex.org/W6640528213","https://openalex.org/W6681005904"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Association":[0],"mining":[1,28,52],"is":[2,30,72],"the":[3,25,35,48,61,73,94,111,117,123,128,137,150,159],"process":[4,114,142,172],"of":[5,17,34,45,78,133],"discovering":[6],"relationships":[7],"between":[8],"items":[9,18,44,62],"in":[10,127,174],"a":[11,15,31,65,157,169],"data":[12],"set,":[13],"where":[14],"group":[16],"forms":[19],"an":[20,79],"itemset.":[21],"A":[22,68],"problem":[23],"with":[24],"typical":[26],"association":[27,51],"approach":[29,71],"large":[32],"number":[33],"generated":[36],"frequent":[37],"itemsets":[38,58],"typically":[39],"do":[40],"not":[41,121],"contain":[42],"any":[43],"interest":[46],"to":[47,92],"user.":[49],"Targeted":[50],"solves":[53],"this":[54,165],"by":[55,116],"only":[56],"deriving":[57],"that":[59,145],"include":[60],"specified":[63],"within":[64],"user's":[66],"query.":[67],"popular":[69],"targeted":[70],"Itemset":[74,95,118,138],"Tree,":[75],"which":[76],"consists":[77],"index":[80],"tree":[81],"structure":[82],"and":[83,87,130,181],"algorithms":[84],"for":[85],"search":[86],"rule":[88,140],"generation.":[89],"Numerous":[90],"enhancements":[91],"improve":[93],"Tree":[96,119,139],"efficiency":[97],"or":[98],"extend":[99],"its":[100],"capability":[101],"have":[102],"been":[103],"proposed.":[104],"However,":[105],"two":[106],"major":[107],"problems":[108],"exist.":[109],"First,":[110],"itemset":[112,176],"generation":[113,132,141,171,177],"utilized":[115],"does":[120],"leverage":[122],"Apriori":[124],"Principle,":[125],"resulting":[126,173],"unnecessary":[129],"costly":[131],"infrequent":[134],"itemsets.":[135],"Second,":[136],"has":[143],"restrictions":[144],"prevent":[146],"some":[147],"rules":[148],"containing":[149],"user":[151,160],"query":[152],"from":[153],"being":[154],"generated;":[155],"as":[156],"result,":[158],"misses":[161],"useful":[162],"information.":[163],"In":[164],"paper,":[166],"we":[167],"offer":[168],"redesigned":[170],"faster":[175],"(milliseconds":[178],"versus":[179],"minutes)":[180],"expanded":[182],"rulesets.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}