{"id":"https://openalex.org/W4389315226","doi":"https://doi.org/10.1109/cog57401.2023.10333151","title":"Visualization-based Iterative Segmentation to Augment Video Game Analytics","display_name":"Visualization-based Iterative Segmentation to Augment Video Game Analytics","publication_year":2023,"publication_date":"2023-08-21","ids":{"openalex":"https://openalex.org/W4389315226","doi":"https://doi.org/10.1109/cog57401.2023.10333151"},"language":"en","primary_location":{"id":"doi:10.1109/cog57401.2023.10333151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog57401.2023.10333151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Conference on Games (CoG)","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/A5066521198","display_name":"Zhaoqing Teng","orcid":"https://orcid.org/0000-0001-8819-5807"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaoqing Teng","raw_affiliation_strings":["University of California Santa Cruz,Santa Cruz,USA","University of California Santa Cruz, Santa Cruz, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Santa Cruz,Santa Cruz,USA","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"University of California Santa Cruz, Santa Cruz, USA","institution_ids":["https://openalex.org/I185103710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087933735","display_name":"Johannes Pfau","orcid":"https://orcid.org/0000-0002-8760-5023"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Johannes Pfau","raw_affiliation_strings":["University of California Santa Cruz,Santa Cruz,USA","University of California Santa Cruz, Santa Cruz, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Santa Cruz,Santa Cruz,USA","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"University of California Santa Cruz, Santa Cruz, USA","institution_ids":["https://openalex.org/I185103710"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087676774","display_name":"Magy Seif El\u2010Nasr","orcid":"https://orcid.org/0000-0002-7808-1686"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Magy Seif El-Nasr","raw_affiliation_strings":["University of California Santa Cruz,Santa Cruz,USA","University of California Santa Cruz, Santa Cruz, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Santa Cruz,Santa Cruz,USA","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"University of California Santa Cruz, Santa Cruz, USA","institution_ids":["https://openalex.org/I185103710"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I185103710"],"apc_list":null,"apc_paid":null,"fwci":0.3641,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68018482,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9940000176429749,"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/T11197","display_name":"Digital Games and Media","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8028290271759033},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7217743992805481},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.6608951687812805},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.5415977835655212},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5361867547035217},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5093408823013306},{"id":"https://openalex.org/keywords/casual","display_name":"Casual","score":0.49956750869750977},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4857042729854584},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.41840633749961853},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.41190049052238464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2910833954811096},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28623294830322266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8028290271759033},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7217743992805481},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.6608951687812805},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.5415977835655212},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5361867547035217},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5093408823013306},{"id":"https://openalex.org/C2781426162","wikidata":"https://www.wikidata.org/wiki/Q2275793","display_name":"Casual","level":2,"score":0.49956750869750977},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4857042729854584},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.41840633749961853},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.41190049052238464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2910833954811096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28623294830322266},{"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cog57401.2023.10333151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog57401.2023.10333151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Conference on Games (CoG)","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":11,"referenced_works":["https://openalex.org/W1971857126","https://openalex.org/W2014700278","https://openalex.org/W2040615834","https://openalex.org/W2146772569","https://openalex.org/W2898502855","https://openalex.org/W3094396102","https://openalex.org/W4206743951","https://openalex.org/W4220926587","https://openalex.org/W4308426654","https://openalex.org/W4366549634","https://openalex.org/W4389315343"],"related_works":["https://openalex.org/W4210310791","https://openalex.org/W2062940763","https://openalex.org/W2937343495","https://openalex.org/W4360833258","https://openalex.org/W3149127250","https://openalex.org/W2158984754","https://openalex.org/W2080934634","https://openalex.org/W2081749267","https://openalex.org/W2112083262","https://openalex.org/W2143428259"],"abstract_inverted_index":{"Within":[0],"the":[1,72,141,169],"field":[2],"of":[3,6,61,70,74,92],"games,":[4],"visualization":[5,91,170],"player":[7,93],"log":[8],"data":[9,103,131],"is":[10,30],"becoming":[11],"an":[12,20,159],"important":[13],"method":[14],"for":[15],"its":[16],"utility":[17],"in":[18,49],"providing":[19],"intuitive":[21],"and":[22,38,54,76,116,171],"informative":[23],"way":[24],"to":[25,52,67,81,114,166],"understand":[26],"players'":[27,101],"experience,":[28],"which":[29],"thus":[31],"often":[32,95,112,127,148],"used":[33],"by":[34],"game":[35,39,88,142],"analytics":[36,51],"personnel":[37],"user":[40],"researchers.":[41],"Moreover,":[42],"even":[43],"players":[44,136,138,173],"themselves":[45],"show":[46],"increased":[47],"interest":[48],"using":[50],"quantify":[53],"self-improve":[55],"their":[56],"performances.":[57],"Among":[58],"other":[59],"types":[60],"visualizations,":[62],"node-edge":[63],"graphs":[64],"have":[65],"proven":[66],"be":[68],"capable":[69],"revealing":[71],"process":[73,102],"individual":[75,124],"aggregated":[77],"players,":[78,123],"allowing":[79],"analysts":[80,165,185],"discover":[82],"play":[83],"patterns":[84],"that":[85,163],"can":[86,186],"inform":[87],"design.":[89],"However,":[90],"traces":[94],"has":[96],"several":[97],"disadvantages.":[98],"First,":[99],"displaying":[100],"does":[104],"not":[105],"trivially":[106],"scale,":[107],"as":[108,150],"tendentially":[109],"high":[110],"variance":[111],"leads":[113],"complex":[115],"abstruse":[117],"graphs.":[118],"Second,":[119],"when":[120],"aggregating":[121],"all":[122],"variations":[125],"are":[126,147],"overlooked.":[128],"For":[129],"example,":[130],"from":[132],"minorities":[133],"(e.g.,":[134],"casual":[135],"or":[137,152,179],"who":[139],"played":[140],"very":[143],"differently":[144],"than":[145],"others)":[146],"treated":[149],"outliers":[151],"noise.":[153],"In":[154],"this":[155,183],"paper,":[156],"we":[157],"present":[158],"iterative":[160],"segmentation":[161],"approach":[162],"allows":[164],"interact":[167],"with":[168],"group":[172],"into":[174],"different":[175],"subcategories":[176],"through":[177],"meta-data":[178],"behavioral":[180],"patterns.":[181],"Using":[182],"approach,":[184],"bypass":[187],"complicated":[188],"visualizations":[189],"while":[190],"protecting":[191],"significant":[192],"unique":[193],"information.":[194]},"counts_by_year":[{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}