{"id":"https://openalex.org/W4392255692","doi":"https://doi.org/10.1145/3633637.3633669","title":"Rare Association Rule Mining Based on Reinforcement Learning","display_name":"Rare Association Rule Mining Based on Reinforcement Learning","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4392255692","doi":"https://doi.org/10.1145/3633637.3633669"},"language":"en","primary_location":{"id":"doi:10.1145/3633637.3633669","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633637.3633669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Computing and Pattern Recognition","raw_type":"proceedings-article"},"type":"conference-paper","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/A5064955724","display_name":"Shengjie Liu","orcid":"https://orcid.org/0009-0007-3211-129X"},"institutions":[{"id":"https://openalex.org/I182707071","display_name":"Ludong University","ror":"https://ror.org/028h95t32","country_code":"CN","type":"education","lineage":["https://openalex.org/I182707071"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengjie Liu","raw_affiliation_strings":["Ludong University, China"],"raw_orcid":"https://orcid.org/0009-0007-3211-129X","affiliations":[{"raw_affiliation_string":"Ludong University, China","institution_ids":["https://openalex.org/I182707071"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051818286","display_name":"Chunjie Zhou","orcid":"https://orcid.org/0009-0006-8436-7193"},"institutions":[{"id":"https://openalex.org/I182707071","display_name":"Ludong University","ror":"https://ror.org/028h95t32","country_code":"CN","type":"education","lineage":["https://openalex.org/I182707071"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunjie Zhou","raw_affiliation_strings":["Ludong University, China"],"raw_orcid":"https://orcid.org/0009-0006-8436-7193","affiliations":[{"raw_affiliation_string":"Ludong University, China","institution_ids":["https://openalex.org/I182707071"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042390764","display_name":"Jialong Li","orcid":"https://orcid.org/0009-0006-7897-3373"},"institutions":[{"id":"https://openalex.org/I182707071","display_name":"Ludong University","ror":"https://ror.org/028h95t32","country_code":"CN","type":"education","lineage":["https://openalex.org/I182707071"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialong Li","raw_affiliation_strings":["Ludong University, China"],"raw_orcid":"https://orcid.org/0009-0006-7897-3373","affiliations":[{"raw_affiliation_string":"Ludong University, China","institution_ids":["https://openalex.org/I182707071"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080959772","display_name":"Xiaoyun Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I182707071","display_name":"Ludong University","ror":"https://ror.org/028h95t32","country_code":"CN","type":"education","lineage":["https://openalex.org/I182707071"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyun Lu","raw_affiliation_strings":["Ludong University, China"],"raw_orcid":"https://orcid.org/0009-0004-2507-7618","affiliations":[{"raw_affiliation_string":"Ludong University, China","institution_ids":["https://openalex.org/I182707071"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I182707071"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"79","last_page":"86"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9997000098228455,"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":0.9997000098228455,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.8885879516601562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7806506156921387},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7359273433685303},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.6510210633277893},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.641669750213623},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.617016077041626},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5922132134437561},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.5541125535964966},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.498974084854126},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4637746214866638},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4397306740283966}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.8885879516601562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7806506156921387},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7359273433685303},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.6510210633277893},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.641669750213623},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.617016077041626},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5922132134437561},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.5541125535964966},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.498974084854126},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4637746214866638},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4397306740283966},{"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/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3633637.3633669","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633637.3633669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Computing and Pattern Recognition","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":29,"referenced_works":["https://openalex.org/W1984607348","https://openalex.org/W1994110553","https://openalex.org/W2102297485","https://openalex.org/W2163230500","https://openalex.org/W2507635762","https://openalex.org/W2746553466","https://openalex.org/W2908261578","https://openalex.org/W2915117209","https://openalex.org/W2949816299","https://openalex.org/W2974887589","https://openalex.org/W3002412300","https://openalex.org/W3009495181","https://openalex.org/W3011959487","https://openalex.org/W3100789280","https://openalex.org/W3102100346","https://openalex.org/W3159562992","https://openalex.org/W3164731060","https://openalex.org/W3169937661","https://openalex.org/W3183523595","https://openalex.org/W3198967093","https://openalex.org/W4206450891","https://openalex.org/W4206988847","https://openalex.org/W4214937699","https://openalex.org/W4220899675","https://openalex.org/W4224220194","https://openalex.org/W4297192969","https://openalex.org/W4297878065","https://openalex.org/W4321071707","https://openalex.org/W4364361247"],"related_works":["https://openalex.org/W4399895933","https://openalex.org/W2161221533","https://openalex.org/W4229699405","https://openalex.org/W1666484574","https://openalex.org/W2216382288","https://openalex.org/W2355491300","https://openalex.org/W4234629551","https://openalex.org/W2011110943","https://openalex.org/W2392697706","https://openalex.org/W366033468"],"abstract_inverted_index":{"In":[0,35,50,66],"some":[1],"cases,":[2,19],"it":[3],"is":[4,33,110,119],"more":[5],"important":[6],"to":[7,57,73,112,120,129,143],"discover":[8],"rare":[9,18,47,59,133,152],"association":[10,48,60,134,153],"rules":[11,16,61,135],"than":[12],"frequent":[13],"itemsets.":[14],"Unique":[15],"represent":[17],"activities":[20,28],"or":[21,76],"events":[22],"in":[23,150,165],"real-world":[24],"applications.":[25],"Extracting":[26],"critical":[27],"from":[29,62,80,94],"massive":[30],"regular":[31],"data":[32,64],"crucial.":[34],"this":[36,67,99,148],"study,":[37],"we":[38],"introduce":[39],"RARM-RL,":[40,51],"a":[41,92],"reinforcement":[42],"learning-based":[43],"approach":[44],"for":[45,162],"discovering":[46],"rules.":[49],"the":[52,63,69,81,89,95,108,114,127,145,156],"environment":[53],"specifies":[54],"iterative":[55],"steps":[56],"extract":[58],"set.":[65],"method,":[68],"agent":[70,90,109,128,170],"takes":[71],"actions":[72,104],"either":[74],"add":[75],"remove":[77],"an":[78,122],"item":[79],"current":[82],"set":[83],"of":[84,147],"items.":[85],"After":[86],"each":[87],"action,":[88],"receives":[91],"reward":[93],"environment.":[96],"By":[97],"repeating":[98],"process":[100],"and":[101,155],"trying":[102],"different":[103,166],"with":[105],"varying":[106],"rewards,":[107],"trained":[111],"maximize":[113],"total":[115],"reward.":[116],"The":[117],"goal":[118],"learn":[121],"optimal":[123],"strategy":[124],"that":[125],"allows":[126],"form":[130],"as":[131,136,169],"many":[132],"possible.":[137],"Extensive":[138],"experiments":[139],"have":[140,158],"been":[141],"conducted":[142],"test":[144],"effectiveness":[146],"method":[149],"mining":[151],"rules,":[154],"results":[157],"shown":[159],"promising":[160],"potential":[161],"its":[163],"applicability":[164],"scenarios":[167],"(such":[168],"transferability).":[171]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}