{"id":"https://openalex.org/W3012796061","doi":"https://doi.org/10.1145/3366423.3380080","title":"Improved Touch-screen Inputting Using Sequence-level Prediction Generation","display_name":"Improved Touch-screen Inputting Using Sequence-level Prediction Generation","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3012796061","doi":"https://doi.org/10.1145/3366423.3380080","mag":"3012796061"},"language":"en","primary_location":{"id":"doi:10.1145/3366423.3380080","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380080","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3366423.3380080","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100327887","display_name":"Xin Wang","orcid":"https://orcid.org/0000-0002-0641-3186"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Wang","raw_affiliation_strings":["Baidu Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101986666","display_name":"Xu Li","orcid":"https://orcid.org/0009-0008-2237-0682"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Li","raw_affiliation_strings":["Baidu Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043981041","display_name":"Jingxin Yu","orcid":"https://orcid.org/0000-0002-4724-0234"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinxing Yu","raw_affiliation_strings":["Baidu Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103150619","display_name":"Mingming Sun","orcid":"https://orcid.org/0000-0002-6199-4905"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingming Sun","raw_affiliation_strings":["Baidu Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435494","display_name":"Ping Li","orcid":"https://orcid.org/0000-0002-1503-0240"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Li","raw_affiliation_strings":["Baidu Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research","institution_ids":["https://openalex.org/I98301712"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5873,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.6828231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3077","last_page":"3083"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9991999864578247,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9991999864578247,"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/T12720","display_name":"Multimedia Communication and Technology","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9887999892234802,"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":0.6617356538772583},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5961043834686279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47179216146469116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35357487201690674}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6617356538772583},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5961043834686279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47179216146469116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35357487201690674},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3366423.3380080","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380080","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3366423.3380080","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380080","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W952608744","https://openalex.org/W1561171833","https://openalex.org/W1607307044","https://openalex.org/W1663973292","https://openalex.org/W1924770834","https://openalex.org/W1967913642","https://openalex.org/W1985554184","https://openalex.org/W2040896124","https://openalex.org/W2051780479","https://openalex.org/W2057900969","https://openalex.org/W2120391124","https://openalex.org/W2124810338","https://openalex.org/W2131588614","https://openalex.org/W2132083787","https://openalex.org/W2140327016","https://openalex.org/W2143355978","https://openalex.org/W2156387975","https://openalex.org/W2156985047","https://openalex.org/W2157331557","https://openalex.org/W2158277448","https://openalex.org/W2251291091","https://openalex.org/W2251942771","https://openalex.org/W2302086703","https://openalex.org/W2529099292","https://openalex.org/W2542835211","https://openalex.org/W2897096909","https://openalex.org/W2962706528","https://openalex.org/W2962979321","https://openalex.org/W2963069010","https://openalex.org/W2964308564","https://openalex.org/W2978329087","https://openalex.org/W2998704965","https://openalex.org/W4251560691"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2],"witnessed":[3],"the":[4,19,37,55,122,129,133],"continuing":[5],"growth":[6],"of":[7,40],"people\u2019s":[8],"dependence":[9],"on":[10,83,114,121],"touchscreen":[11],"devices.":[12],"As":[13],"a":[14,45,60,88,95,115],"result,":[15],"input":[16,41,47,52,105],"speed":[17],"with":[18,44],"onscreen":[20],"keyboard":[21],"has":[22],"become":[23],"crucial":[24],"to":[25,66,103],"communication":[26],"efficiency":[27,53],"and":[28,110],"user":[29],"experience.":[30],"In":[31],"this":[32],"work,":[33],"we":[34,58,92],"formally":[35],"discuss":[36],"general":[38],"problem":[39],"expectation":[42],"prediction":[43],"touch-screen":[46],"method":[48],"editor":[49],"(IME).":[50],"Taken":[51],"as":[54,73,75],"optimization":[56],"target,":[57],"proposed":[59,108,130],"neural":[61],"end-to-end":[62],"candidates":[63],"generation":[64],"solution":[65],"handle":[67],"automatic":[68],"correction,":[69],"reordering,":[70],"insertion,":[71],"deletion":[72],"well":[74],"completion.":[76],"Evaluation":[77],"metrics":[78],"are":[79,112],"also":[80,93],"discussed":[81],"base":[82],"real":[84],"use":[85],"scenarios.":[86],"For":[87],"more":[89],"thorough":[90],"comparison,":[91],"provide":[94],"statistical":[96],"strategy":[97],"for":[98],"mapping":[99],"touch":[100],"coordinate":[101],"sequences":[102],"text":[104],"candidates.":[106],"The":[107,118],"model":[109,131],"baselines":[111],"evaluated":[113],"real-world":[116],"dataset.":[117],"experiment":[119],"(conducted":[120],"PaddlePaddle":[123],"deep":[124],"learning":[125],"platform1)":[126],"shows":[127],"that":[128],"outperforms":[132],"baselines.":[134]},"counts_by_year":[{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}