{"id":"https://openalex.org/W4288080216","doi":"https://doi.org/10.1145/3394486.3403367","title":"Cracking the Black Box","display_name":"Cracking the Black Box","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W4288080216","doi":"https://doi.org/10.1145/3394486.3403367"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403367","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","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/A5060002954","display_name":"Xiangyu Sun","orcid":"https://orcid.org/0000-0002-3417-9323"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xiangyu Sun","raw_affiliation_strings":["Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053177492","display_name":"Jack Davis","orcid":null},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jack Davis","raw_affiliation_strings":["Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026297632","display_name":"Oliver Schulte","orcid":"https://orcid.org/0000-0002-2805-4313"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Oliver Schulte","raw_affiliation_strings":["Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067654997","display_name":"Guiliang Liu","orcid":"https://orcid.org/0000-0001-7464-523X"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Guiliang Liu","raw_affiliation_strings":["Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I18014758"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3154","last_page":"3162"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9909999966621399,"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":0.989799976348877,"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/computer-science","display_name":"Computer science","score":0.8088395595550537},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7069265842437744},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7046573758125305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6681321263313293},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.6655844449996948},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5538896322250366},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5485551953315735},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5166919231414795},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.46935492753982544},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4528352916240692},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.44679075479507446},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4346614181995392},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.4245249927043915},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.35241788625717163},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32518792152404785}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8088395595550537},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7069265842437744},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7046573758125305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6681321263313293},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6655844449996948},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5538896322250366},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5485551953315735},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5166919231414795},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.46935492753982544},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4528352916240692},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.44679075479507446},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4346614181995392},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.4245249927043915},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35241788625717163},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32518792152404785},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3403367","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1492518272","https://openalex.org/W1497569129","https://openalex.org/W1529331786","https://openalex.org/W1930624869","https://openalex.org/W2066442872","https://openalex.org/W2076508878","https://openalex.org/W2099302642","https://openalex.org/W2106524649","https://openalex.org/W2134797427","https://openalex.org/W2135582063","https://openalex.org/W2136464549","https://openalex.org/W2181817108","https://openalex.org/W2621053657","https://openalex.org/W2793959751","https://openalex.org/W2806905225","https://openalex.org/W2963852406","https://openalex.org/W2964250377","https://openalex.org/W3029534136","https://openalex.org/W3098369568","https://openalex.org/W3139377883","https://openalex.org/W4237372041","https://openalex.org/W4256300792","https://openalex.org/W4287867253","https://openalex.org/W6766726207"],"related_works":["https://openalex.org/W2280422768","https://openalex.org/W3143197806","https://openalex.org/W4377865163","https://openalex.org/W4312601715","https://openalex.org/W4392828243","https://openalex.org/W4298185893","https://openalex.org/W4312822655","https://openalex.org/W3157170264","https://openalex.org/W2896078964","https://openalex.org/W4281399026"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,49,64,67,74,136],"trade-off":[4],"between":[5],"Accuracy":[6],"and":[7,25,41,59,72,113,122,126],"Transparency":[8],"for":[9,116],"deep":[10,23,69],"learning":[11,70,132],"applied":[12],"to":[13,35,44,134],"sports":[14,29],"analytics.":[15,30],"Neural":[16],"nets":[17],"achieve":[18],"great":[19],"predictive":[20],"accuracy":[21],"through":[22],"learning,":[24],"are":[26],"popular":[27],"in":[28,52,77],"But":[31],"it":[32],"is":[33,85],"hard":[34],"interpret":[36],"a":[37,57,86,92,98,105],"neural":[38,106],"net":[39],"model":[40,61,71,84,88,130],"harder":[42],"still":[43],"extract":[45],"actionable":[46],"insights":[47,115],"from":[48,139],"knowledge":[50,76],"implicit":[51],"it.":[53],"Therefore,":[54],"we":[55],"built":[56],"simple":[58],"transparent":[60],"that":[62],"mimics":[63],"output":[65],"of":[66,94,104,143],"original":[68],"represents":[73],"learned":[75],"an":[78],"explicit":[79],"interpretable":[80],"way.":[81],"Our":[82],"mimic":[83],"linear":[87,95],"tree,":[89],"which":[90],"combines":[91],"collection":[93],"models":[96],"with":[97,141],"regression-tree":[99],"structure.":[100],"The":[101],"tree":[102,131],"version":[103],"network":[107],"achieves":[108],"high":[109],"fidelity,":[110],"explains":[111],"itself,":[112],"produces":[114],"expert":[117],"stakeholders":[118],"such":[119],"as":[120],"athletes":[121],"coaches.":[123],"We":[124],"propose":[125],"compare":[127],"several":[128],"scalable":[129],"heuristics":[133],"address":[135],"computational":[137],"challenge":[138],"datasets":[140],"millions":[142],"data":[144],"points.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-07-28T00:00:00"}
