{"id":"https://openalex.org/W3038362670","doi":"https://doi.org/10.1145/3404512.3404513","title":"A Random Forest Regression Model Predicting the Winners of Summer Olympic Events","display_name":"A Random Forest Regression Model Predicting the Winners of Summer Olympic Events","publication_year":2020,"publication_date":"2020-05-29","ids":{"openalex":"https://openalex.org/W3038362670","doi":"https://doi.org/10.1145/3404512.3404513","mag":"3038362670"},"language":"en","primary_location":{"id":"doi:10.1145/3404512.3404513","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404512.3404513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big Data Engineering","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/A5001851121","display_name":"Mengjie Jia","orcid":"https://orcid.org/0009-0003-6988-2195"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengjie Jia","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101429223","display_name":"Yue Zhao","orcid":"https://orcid.org/0000-0002-9280-9469"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhao","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015345884","display_name":"Furong Chang","orcid":"https://orcid.org/0000-0002-1558-4120"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Furong Chang","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006352222","display_name":"Bofeng Zhang","orcid":"https://orcid.org/0000-0002-5001-1096"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bofeng Zhang","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048013499","display_name":"Kenji Yoshigoe","orcid":null},"institutions":[{"id":"https://openalex.org/I158123994","display_name":"Toyo University","ror":"https://ror.org/059d6yn51","country_code":"JP","type":"education","lineage":["https://openalex.org/I158123994"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenji Yoshigoe","raw_affiliation_strings":["Toyo University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyo University, Tokyo, Japan","institution_ids":["https://openalex.org/I158123994"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.08712738,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"62","last_page":"69"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9973000288009644,"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":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/medal","display_name":"Medal","score":0.9754528999328613},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6517224907875061},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.5576335787773132},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.5362154245376587},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.49136510491371155},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4532831311225891},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4264715909957886},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4208652675151825},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.39345329999923706},{"id":"https://openalex.org/keywords/regional-science","display_name":"Regional science","score":0.34403011202812195},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.33305269479751587},{"id":"https://openalex.org/keywords/demography","display_name":"Demography","score":0.3023349642753601},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2827654480934143},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1630750298500061},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.1374254822731018},{"id":"https://openalex.org/keywords/archaeology","display_name":"Archaeology","score":0.09945449233055115}],"concepts":[{"id":"https://openalex.org/C2777867650","wikidata":"https://www.wikidata.org/wiki/Q131647","display_name":"Medal","level":2,"score":0.9754528999328613},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6517224907875061},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.5576335787773132},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.5362154245376587},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.49136510491371155},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4532831311225891},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4264715909957886},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4208652675151825},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.39345329999923706},{"id":"https://openalex.org/C148383697","wikidata":"https://www.wikidata.org/wiki/Q1781695","display_name":"Regional science","level":1,"score":0.34403011202812195},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.33305269479751587},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.3023349642753601},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2827654480934143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1630750298500061},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.1374254822731018},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.09945449233055115}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3404512.3404513","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404512.3404513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big Data Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W577552570","https://openalex.org/W1480376833","https://openalex.org/W1481980187","https://openalex.org/W1996106371","https://openalex.org/W2039493274","https://openalex.org/W2055369505","https://openalex.org/W2063524846","https://openalex.org/W2079473977","https://openalex.org/W2113242816","https://openalex.org/W2122739133","https://openalex.org/W2143584315","https://openalex.org/W2161413552","https://openalex.org/W2387117385","https://openalex.org/W2390526642","https://openalex.org/W2736669548","https://openalex.org/W2886287939","https://openalex.org/W4256300792"],"related_works":["https://openalex.org/W2048488252","https://openalex.org/W2940614149","https://openalex.org/W4288365262","https://openalex.org/W2787485953","https://openalex.org/W3217432596","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543"],"abstract_inverted_index":{"From":[0],"the":[1,10,32,36,42,53,56,60,73,75,81,85,97,108,112,115,121],"past":[2],"Olympic":[3,37,65,124],"medal":[4,38,57],"lists,":[5],"we":[6,24,51],"can":[7],"find":[8],"that":[9,27],"number":[11,98],"of":[12,14,35,55,77,99,111,117],"medals":[13],"China":[15],"has":[16],"been":[17],"increasing":[18],"steadily":[19],"in":[20,120],"recent":[21],"years":[22],"while":[23],"also":[25],"observe":[26],"some":[28,118],"countries":[29],"always":[30],"occupy":[31],"top":[33],"positions":[34],"list,":[39],"such":[40],"as":[41,67,84],"United":[43],"States,":[44],"Britain":[45],"and":[46,70,80],"Germany.":[47],"In":[48],"this":[49],"work":[50],"take":[52],"data":[54],"lists":[58],"from":[59],"18th":[61],"to":[62,88,95,106],"31st":[63],"Summer":[64],"Games":[66,125],"a":[68,90],"sample":[69],"selects":[71],"GDP,":[72],"population,":[74],"size":[76],"national":[78],"team":[79],"home":[82],"advantage":[83],"characteristic":[86],"parameters":[87],"build":[89],"random":[91],"forest":[92],"regression":[93],"model":[94],"predict":[96],"medals.":[100],"The":[101],"FP-growth":[102],"algorithm":[103],"is":[104],"used":[105],"analyze":[107],"association":[109],"rules":[110],"data.":[113],"And":[114],"winners":[116],"events":[119],"2020":[122],"Tokyo":[123],"are":[126],"predicted.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
