{"id":"https://openalex.org/W4207063353","doi":"https://doi.org/10.1109/icdm51629.2021.00163","title":"Alternative Ruleset Discovery to Support Black-box Model Predictions","display_name":"Alternative Ruleset Discovery to Support Black-box Model Predictions","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4207063353","doi":"https://doi.org/10.1109/icdm51629.2021.00163"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm51629.2021.00163","pdf_url":null,"source":{"id":"https://openalex.org/S4363608061","display_name":"2021 IEEE International Conference on Data Mining (ICDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5073627801","display_name":"Yoichi Sasaki","orcid":"https://orcid.org/0000-0002-7596-773X"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"funder","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoichi Sasaki","raw_affiliation_strings":["NEC Corporation, Kawasaki, Japan"],"affiliations":[{"raw_affiliation_string":"NEC Corporation, Kawasaki, Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040827276","display_name":"Yuzuru Okajima","orcid":"https://orcid.org/0000-0003-3973-2041"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"funder","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuzuru Okajima","raw_affiliation_strings":["NEC Corporation, Kawasaki, Japan"],"affiliations":[{"raw_affiliation_string":"NEC Corporation, Kawasaki, Japan","institution_ids":["https://openalex.org/I118347220"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.393,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.469485,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":75,"max":78},"biblio":{"volume":null,"issue":null,"first_page":"1312","last_page":"1317"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9994,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9994,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9849,"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"}},{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9834,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8730707},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.82935894},{"id":"https://openalex.org/keywords/post-hoc","display_name":"Post hoc","score":0.53955287}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8730707},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.82935894},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.675422},{"id":"https://openalex.org/C2992886853","wikidata":"https://www.wikidata.org/wiki/Q18381816","display_name":"Post hoc","level":2,"score":0.53955287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49540102},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47611174},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.47175178},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3334055},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.14062905},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.094314694},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C199343813","wikidata":"https://www.wikidata.org/wiki/Q12128","display_name":"Dentistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm51629.2021.00163","pdf_url":null,"source":{"id":"https://openalex.org/S4363608061","display_name":"2021 IEEE International Conference on Data Mining (ICDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions","score":0.79}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":18,"referenced_works":["https://openalex.org/W2079104779","https://openalex.org/W2166566648","https://openalex.org/W2282821441","https://openalex.org/W2616268764","https://openalex.org/W2619325105","https://openalex.org/W2744365997","https://openalex.org/W2788403449","https://openalex.org/W2904994710","https://openalex.org/W2944540640","https://openalex.org/W2962772482","https://openalex.org/W2962862931","https://openalex.org/W2963292722","https://openalex.org/W2963463132","https://openalex.org/W2964112969","https://openalex.org/W3037729706","https://openalex.org/W3038082613","https://openalex.org/W3091600846","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W4387589990","https://openalex.org/W4382240676","https://openalex.org/W4297660007","https://openalex.org/W4241566321","https://openalex.org/W3101055019","https://openalex.org/W2943982549","https://openalex.org/W2910028250","https://openalex.org/W2886918272","https://openalex.org/W2797441709","https://openalex.org/W2346578521"],"abstract_inverted_index":{"The":[0,142],"increasing":[1],"attention":[2],"to":[3,12,17,84,97,148,162,178,193,235],"the":[4,13,19,115,122,136,171,221,236,243],"interpretability":[5],"of":[6,15,21,138,200,241],"machine":[7],"learning":[8],"models":[9,23],"has":[10,65],"led":[11],"development":[14],"methods":[16],"explain":[18],"behavior":[20],"black-box":[22,105,140],"in":[24,48,167],"a":[25,33,57,80,86,92,103,118,139,179,194],"post-hoc":[26,30],"manner.":[27],"However,":[28,169],"such":[29,219],"approaches":[31],"generate":[32],"new":[34,38],"explanation":[35,61,82,111,131],"for":[36,62,73,135,152,230],"every":[37,99],"input,":[39],"and":[40],"these":[41],"explanations":[42],"cannot":[43,70],"be":[44,71,159,163,191,205],"checked":[45],"by":[46,102,165],"humans":[47,166],"advance.":[49,168],"A":[50],"method":[51,83,215,238],"that":[52,113,120,187,213,220],"selects":[53,114],"decision":[54,93],"rules":[55,222],"from":[56,90,117,224],"finite":[58,88],"ruleset":[59,89,143,172],"as":[60,128,233],"neural":[63],"networks":[64],"been":[66],"proposed,":[67],"but":[68,155],"it":[69,156],"used":[72],"other":[74],"models.In":[75],"this":[76,125,188],"paper,":[77],"we":[78,108,185],"propose":[79],"model-agnostic":[81],"find":[85],"pre-verifiable":[87],"which":[91,203],"rule":[94,126],"is":[95],"selected":[96,223],"support":[98],"prediction":[100,137],"made":[101],"given":[104],"model.":[106,141],"First,":[107],"define":[109],"an":[110,129],"model":[112],"rule,":[116],"ruleset,":[119],"gives":[121],"closest":[123],"prediction;":[124],"works":[127],"alternative":[130],"or":[132],"supportive":[133],"evidence":[134],"should":[144,157],"have":[145],"high":[146,175],"coverage":[147,176],"give":[149],"close":[150],"predictions":[151],"future":[153],"inputs,":[154],"also":[158],"small":[160,217],"enough":[161],"checkable":[164],"minimizing":[170],"while":[173],"keeping":[174],"leads":[177],"computationally":[180],"hard":[181],"combinatorial":[182],"problem.":[183],"Hence,":[184],"show":[186],"problem":[189,197],"can":[190,204,226],"reduced":[192],"weighted":[195],"MaxSAT":[196],"composed":[198],"only":[199],"Horn":[201],"clauses,":[202],"efficiently":[206],"solved":[207],"with":[208],"modern":[209],"solvers.Experimental":[210],"results":[211],"showed":[212],"our":[214],"found":[216],"rulesets":[218,240],"them":[225],"achieve":[227],"higher":[228],"accuracy":[229],"structured":[231],"data":[232],"compared":[234],"existing":[237],"using":[239],"almost":[242],"same":[244],"size.":[245]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4207063353","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-04-15T22:46:22.419185","created_date":"2022-01-26"}