{"id":"https://openalex.org/W2611531483","doi":"https://doi.org/10.1145/3025453.3025701","title":"Word Clarity as a Metric in Sampling Keyboard Test Sets","display_name":"Word Clarity as a Metric in Sampling Keyboard Test Sets","publication_year":2017,"publication_date":"2017-05-02","ids":{"openalex":"https://openalex.org/W2611531483","doi":"https://doi.org/10.1145/3025453.3025701","mag":"2611531483"},"language":"en","primary_location":{"id":"doi:10.1145/3025453.3025701","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3025453.3025701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems","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/A5068034013","display_name":"Xin Yi","orcid":"https://orcid.org/0000-0001-8041-7962"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Yi","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043272273","display_name":"Chun Yu","orcid":"https://orcid.org/0000-0003-2591-7993"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Yu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001500946","display_name":"Weinan Shi","orcid":"https://orcid.org/0000-0002-1351-9034"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weinan Shi","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016901770","display_name":"Xiaojun Bi","orcid":"https://orcid.org/0000-0002-9716-7709"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaojun Bi","raw_affiliation_strings":["Stony Brook University, Stony Brook, NY, USA"],"affiliations":[{"raw_affiliation_string":"Stony Brook University, Stony Brook, NY, USA","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057896400","display_name":"Yuanchun Shi","orcid":"https://orcid.org/0000-0003-2273-6927"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanchun Shi","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5068034013"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.9393,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.9112782,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4216","last_page":"4228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10789","display_name":"Interactive and Immersive Displays","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10789","display_name":"Interactive and Immersive Displays","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10470","display_name":"Usability and User Interface Design","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/clarity","display_name":"CLARITY","score":0.919925332069397},{"id":"https://openalex.org/keywords/bigram","display_name":"Bigram","score":0.8428640365600586},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7424424886703491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6914151310920715},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.679908037185669},{"id":"https://openalex.org/keywords/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.6691180467605591},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5300498008728027},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4378972053527832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.432756245136261},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.42777860164642334},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3950076997280121},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3082469701766968},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24043118953704834},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08260208368301392}],"concepts":[{"id":"https://openalex.org/C2777146004","wikidata":"https://www.wikidata.org/wiki/Q14949826","display_name":"CLARITY","level":2,"score":0.919925332069397},{"id":"https://openalex.org/C108757681","wikidata":"https://www.wikidata.org/wiki/Q2773912","display_name":"Bigram","level":3,"score":0.8428640365600586},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7424424886703491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6914151310920715},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.679908037185669},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.6691180467605591},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5300498008728027},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4378972053527832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.432756245136261},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42777860164642334},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3950076997280121},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3082469701766968},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24043118953704834},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08260208368301392},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3025453.3025701","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3025453.3025701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems","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":41,"referenced_works":["https://openalex.org/W33420468","https://openalex.org/W155995321","https://openalex.org/W1550321890","https://openalex.org/W1968512144","https://openalex.org/W1999806644","https://openalex.org/W2001340812","https://openalex.org/W2010376411","https://openalex.org/W2012205861","https://openalex.org/W2013138719","https://openalex.org/W2015509928","https://openalex.org/W2022422334","https://openalex.org/W2022523395","https://openalex.org/W2032505690","https://openalex.org/W2051780479","https://openalex.org/W2052570369","https://openalex.org/W2058049219","https://openalex.org/W2066914485","https://openalex.org/W2069657084","https://openalex.org/W2077940530","https://openalex.org/W2098924240","https://openalex.org/W2099287431","https://openalex.org/W2103751734","https://openalex.org/W2104328027","https://openalex.org/W2106931201","https://openalex.org/W2107655853","https://openalex.org/W2113893685","https://openalex.org/W2118711147","https://openalex.org/W2124810338","https://openalex.org/W2131588614","https://openalex.org/W2131955678","https://openalex.org/W2133119840","https://openalex.org/W2133990837","https://openalex.org/W2146099004","https://openalex.org/W2148723390","https://openalex.org/W2165645720","https://openalex.org/W2166481425","https://openalex.org/W2166668780","https://openalex.org/W2169710492","https://openalex.org/W2179427518","https://openalex.org/W4239127880","https://openalex.org/W4255375128"],"related_works":["https://openalex.org/W2065474030","https://openalex.org/W3173084154","https://openalex.org/W2982021180","https://openalex.org/W2251497876","https://openalex.org/W2241081188","https://openalex.org/W2128567707","https://openalex.org/W2011383762","https://openalex.org/W2035962958","https://openalex.org/W2146546639","https://openalex.org/W2197825247"],"abstract_inverted_index":{"Test":[0],"sets":[1,41,117,138],"play":[2],"an":[3],"essential":[4],"role":[5],"in":[6,17,98,104],"evaluating":[7],"text":[8,88],"entry":[9,89],"techniques.":[10],"In":[11],"this":[12],"paper,":[13],"we":[14],"argue":[15],"that":[16,80],"addition":[18],"to":[19,51,57,95],"the":[20,43,49,123,132,142],"widely":[21],"adopted":[22],"metric":[23,37],"of":[24,131],"bigram":[25,127],"representativeness":[26],"and":[27,74,77,101,126,129],"memorability,":[28],"word":[29,54,68,81,124],"clarity":[30,47,82,125],"should":[31],"also":[32],"be":[33],"considered":[34],"as":[35],"a":[36,53,63,84,110],"when":[38],"creating":[39],"test":[40,116,133,137],"from":[42],"target":[44],"dataset.":[45],"Word":[46],"quantifies":[48],"extent":[50],"which":[52,121],"is":[55],"likely":[56],"confuse":[58],"with":[59,118],"other":[60],"words":[61],"on":[62,87,141],"keyboard.":[64],"We":[65,107],"formally":[66],"define":[67],"clarity,":[69],"derive":[70],"equations":[71],"calculating":[72],"it,":[73],"both":[75],"theoretically":[76],"empirically":[78],"show":[79],"has":[83],"significant":[85],"effect":[86],"performance:":[90],"it":[91],"can":[92],"yield":[93],"up":[94],"26.4%":[96],"difference":[97,103],"error":[99],"rate,":[100],"25%":[102],"input":[105],"speed.":[106],"later":[108],"propose":[109],"Pareto":[111],"optimization":[112],"method":[113],"for":[114],"sampling":[115],"different":[119],"sizes,":[120],"optimizes":[122],"representativeness,":[128],"memorability":[130],"set.":[134],"The":[135],"obtained":[136],"are":[139],"published":[140],"Internet.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
