{"id":"https://openalex.org/W4413393849","doi":"https://doi.org/10.1109/whc64065.2025.11123249","title":"Simulation-Guided Subset Aggregation for Large-Scale Tacton Similarity Ratings","display_name":"Simulation-Guided Subset Aggregation for Large-Scale Tacton Similarity Ratings","publication_year":2025,"publication_date":"2025-07-08","ids":{"openalex":"https://openalex.org/W4413393849","doi":"https://doi.org/10.1109/whc64065.2025.11123249"},"language":"en","primary_location":{"id":"doi:10.1109/whc64065.2025.11123249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whc64065.2025.11123249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE World Haptics Conference (WHC)","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/A5019339490","display_name":"Chungman Lim","orcid":"https://orcid.org/0000-0002-7857-3322"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Chungman Lim","raw_affiliation_strings":["AI Graduate School Gwangju Institute of Science and Technology,Gwangju,South Korea"],"affiliations":[{"raw_affiliation_string":"AI Graduate School Gwangju Institute of Science and Technology,Gwangju,South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043917822","display_name":"Hasti Seifi","orcid":"https://orcid.org/0000-0001-6437-0463"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hasti Seifi","raw_affiliation_strings":["School of Computing and Augmented Intelligence Arizona State University,Tempe,USA"],"affiliations":[{"raw_affiliation_string":"School of Computing and Augmented Intelligence Arizona State University,Tempe,USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038111573","display_name":"Gunhyuk Park","orcid":"https://orcid.org/0000-0003-2677-5907"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gunhyuk Park","raw_affiliation_strings":["School of AI Convergence Gwangju Institute of Science and Technology,Gwangju,South Korea"],"affiliations":[{"raw_affiliation_string":"School of AI Convergence Gwangju Institute of Science and Technology,Gwangju,South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019339490"],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26155046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"102","last_page":"114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.8360999822616577,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.8360999822616577,"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/T10320","display_name":"Neural Networks and Applications","score":0.8166000247001648,"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/similarity","display_name":"Similarity (geometry)","score":0.6475322246551514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6115103960037231},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5603612065315247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3970631957054138},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32571762800216675},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07656100392341614}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6475322246551514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6115103960037231},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5603612065315247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3970631957054138},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32571762800216675},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07656100392341614},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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:10.1109/whc64065.2025.11123249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whc64065.2025.11123249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE World Haptics Conference (WHC)","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":35,"referenced_works":["https://openalex.org/W1516623623","https://openalex.org/W1531817010","https://openalex.org/W1577704899","https://openalex.org/W1965985440","https://openalex.org/W1993450913","https://openalex.org/W2017305511","https://openalex.org/W2025904705","https://openalex.org/W2055137451","https://openalex.org/W2056369490","https://openalex.org/W2072096504","https://openalex.org/W2088508619","https://openalex.org/W2092607849","https://openalex.org/W2121600979","https://openalex.org/W2125517406","https://openalex.org/W2259691514","https://openalex.org/W2345327032","https://openalex.org/W2572904480","https://openalex.org/W2604801274","https://openalex.org/W2790493375","https://openalex.org/W2791238579","https://openalex.org/W2796280382","https://openalex.org/W2948943639","https://openalex.org/W2957125216","https://openalex.org/W2970355225","https://openalex.org/W3022413497","https://openalex.org/W3163595989","https://openalex.org/W3193405041","https://openalex.org/W4206937511","https://openalex.org/W4250124742","https://openalex.org/W4285277465","https://openalex.org/W4366547404","https://openalex.org/W4366549547","https://openalex.org/W4385820054","https://openalex.org/W4390772381","https://openalex.org/W4396831967"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Exploring":[0],"perceptual":[1,61,166],"dissimilarity":[2],"spaces":[3,62,167],"of":[4,14,195],"large-scale":[5,59,121,169],"Tactons":[6],"(i.e.,":[7],"Tactile":[8],"icons)":[9],"can":[10,158],"inform":[11],"the":[12,34,136,185,193],"design":[13],"distinguishable":[15],"haptic":[16],"feedback.":[17],"Yet,":[18],"collecting":[19],"pairwise":[20],"similarity":[21,81],"ratings":[22],"for":[23,36,140,168,189],"entire":[24],"Tacton":[25,60,93,113,170],"sets":[26,114],"becomes":[27],"costly":[28],"as":[29],"set":[30,122],"size":[31,52],"increases,":[32],"prompting":[33],"need":[35],"alternative":[37],"methods":[38],"like":[39],"subset":[40,51,108,161,196],"aggregation.":[41],"Despite":[42],"previous":[43],"efforts,":[44],"little":[45],"systematic":[46],"investigation":[47],"exists":[48],"on":[49],"efficient":[50],"or":[53,116],"participant":[54],"number":[55],"needed":[56],"to":[57,98,164,177,184],"estimate":[58],"within":[63],"a":[64,74],"bounded":[65],"error":[66],"threshold.":[67],"We":[68,134,191],"address":[69],"this":[70],"gap":[71],"by":[72,103],"introducing":[73],"model":[75,84,151],"that":[76,128,156],"simulates":[77],"between-subject":[78],"variability":[79],"in":[80,146],"perception.":[82],"The":[83,149],"explores":[85],"various":[86],"distributions":[87],"under":[88],"different":[89],"conditions,":[90,142],"including":[91],"total":[92],"numbers":[94],"and":[95,119,143,198],"subset-to-total":[96],"ratios,":[97],"guide":[99],"user":[100],"studies.":[101,148],"Guided":[102],"these":[104],"simulations,":[105],"we":[106],"evaluated":[107],"aggregation":[109,162,197],"with":[110],"three":[111],"small-scale":[112],"(12":[115],"14":[117],"patterns)":[118],"one":[120],"(48":[123],"patterns).":[124],"Study":[125],"1":[126],"revealed":[127],"initial":[129],"simulations":[130,139],"underestimated":[131],"real-world":[132],"variability.":[133],"refined":[135],"model,":[137],"ran":[138],"larger-scale":[141],"validated":[144],"them":[145],"subsequent":[147],"updated":[150],"closely":[152],"matched":[153],"reality,":[154],"showing":[155],"designers":[157],"use":[159],"our":[160],"method":[163],"prototype":[165],"sets.":[171],"Notably,":[172],"4\u20137":[173],"observations":[174],"were":[175],"sufficient":[176],"achieve":[178],"<tex":[179],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[180],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\rho\\geq":[181],"0.6$</tex>,":[182],"compared":[183],"typical":[186],"12":[187],"required":[188],"generalization.":[190],"discuss":[192],"efficacy":[194],"future":[199],"research":[200],"directions.":[201]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
