{"id":"https://openalex.org/W2535842943","doi":"https://doi.org/10.1145/2984511.2984543","title":"Mining Controller Inputs to Understand Gameplay","display_name":"Mining Controller Inputs to Understand Gameplay","publication_year":2016,"publication_date":"2016-10-16","ids":{"openalex":"https://openalex.org/W2535842943","doi":"https://doi.org/10.1145/2984511.2984543","mag":"2535842943"},"language":"en","primary_location":{"id":"doi:10.1145/2984511.2984543","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2984511.2984543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th Annual Symposium on User Interface Software and Technology","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/A5063454149","display_name":"Brian A. Smith","orcid":"https://orcid.org/0000-0003-2540-0839"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian A. Smith","raw_affiliation_strings":["Columbia University, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York City, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051975921","display_name":"Shree K. Nayar","orcid":"https://orcid.org/0000-0002-6452-6998"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shree K. Nayar","raw_affiliation_strings":["Columbia University, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York City, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":0.9706,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78940439,"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":"157","last_page":"168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9994999766349792,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9994999766349792,"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/T11674","display_name":"Sports Analytics and Performance","score":0.9944000244140625,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8044335246086121},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6616035103797913},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.6369851231575012},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.6139130592346191},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5690973997116089},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.49952101707458496},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.43255606293678284},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.3238478899002075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32250893115997314},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.24354493618011475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8044335246086121},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6616035103797913},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.6369851231575012},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.6139130592346191},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5690973997116089},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.49952101707458496},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.43255606293678284},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.3238478899002075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32250893115997314},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.24354493618011475},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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:10.1145/2984511.2984543","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2984511.2984543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th Annual Symposium on User Interface Software and Technology","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":33,"referenced_works":["https://openalex.org/W1880262756","https://openalex.org/W1985626820","https://openalex.org/W1989249972","https://openalex.org/W1998668407","https://openalex.org/W2001340812","https://openalex.org/W2013363278","https://openalex.org/W2020842694","https://openalex.org/W2038002297","https://openalex.org/W2051356579","https://openalex.org/W2057674248","https://openalex.org/W2068687483","https://openalex.org/W2075773711","https://openalex.org/W2079194772","https://openalex.org/W2098126593","https://openalex.org/W2108903791","https://openalex.org/W2110027950","https://openalex.org/W2113410615","https://openalex.org/W2130339025","https://openalex.org/W2134300284","https://openalex.org/W2134665698","https://openalex.org/W2135541598","https://openalex.org/W2141104189","https://openalex.org/W2142777385","https://openalex.org/W2146078527","https://openalex.org/W2146772569","https://openalex.org/W2149390557","https://openalex.org/W2161610563","https://openalex.org/W2174706414","https://openalex.org/W2223017844","https://openalex.org/W2582777894","https://openalex.org/W2759626748","https://openalex.org/W2963977107","https://openalex.org/W4299998071"],"related_works":["https://openalex.org/W4312773271","https://openalex.org/W4315588616","https://openalex.org/W2769501189","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W3159709618","https://openalex.org/W2611137333","https://openalex.org/W3005513013","https://openalex.org/W4389543811"],"abstract_inverted_index":{"Today's":[0],"game":[1,56,85,92],"analytics":[2],"systems":[3],"are":[4,15,190],"powered":[5],"by":[6],"event":[7],"logs,":[8],"which":[9],"reveal":[10],"information":[11,108],"about":[12,21,159,188,208],"what":[13],"players":[14,132,202],"doing":[16],"but":[17],"offer":[18],"little":[19],"insight":[20],"the":[22,30,60,79,88,115,141,147,154,179],"types":[23,61,80,156],"of":[24,32,62,81,97,118,157,167,194,211],"gameplay":[25,33,63,119,125,160,189],"that":[26,46,83,90,111,126,131,164,185],"games":[27,69],"foster.":[28],"Moreover,":[29],"concept":[31],"itself":[34],"is":[35,127,165],"difficult":[36],"to":[37,58,109,121,129,152,183],"define":[38],"and":[39,87,120],"quantify.":[40],"In":[41],"this":[42,107],"paper,":[43],"we":[44],"show":[45],"analyzing":[47],"players'":[48],"controller":[49],"inputs":[50],"using":[51],"probabilistic":[52],"topic":[53,143],"models":[54],"allows":[55],"developers":[57,76],"describe":[59],"--":[64,67],"or":[65],"action":[66,82,149],"in":[68,70,100,161,191,207],"a":[71,84,162,174],"quantitative":[72],"way.":[73],"More":[74],"specifically,":[75],"can":[77,105],"discover":[78],"fosters":[86,94],"extent":[89],"each":[91,95,168,195],"level":[93],"type":[96],"action,":[98],"all":[99],"an":[101],"unsupervised":[102],"manner.":[103],"They":[104],"use":[106],"verify":[110,184],"their":[112],"levels":[113,123,130],"feature":[114],"appropriate":[116],"style":[117],"recommend":[122],"with":[124,136,203],"similar":[128],"like.":[133],"We":[134,172],"begin":[135],"latent":[137],"Dirichlet":[138],"allocation":[139],"(LDA),":[140],"simplest":[142],"model,":[144],"then":[145],"develop":[146],"player-gameplay":[148],"(PGA)":[150],"model":[151],"make":[153],"same":[155],"discoveries":[158,187],"way":[163],"independent":[166,193],"player's":[169,196],"play":[170,197],"style.":[171,198],"train":[173],"player":[175],"recognition":[176],"system":[177,200],"on":[178],"PGA":[180],"model's":[181],"output":[182],"its":[186],"fact":[192],"The":[199],"recognizes":[201],"over":[204],"90%":[205],"accuracy":[206],"20":[209],"seconds":[210],"playtime.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}