{"id":"https://openalex.org/W4416250576","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227368","title":"Revisiting the Knowledge Recall and Selection in Chinese Spelling Correction","display_name":"Revisiting the Knowledge Recall and Selection in Chinese Spelling Correction","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250576","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227368"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5034561410","display_name":"Zhengxu Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhengxu Hou","raw_affiliation_strings":["Alibaba,Digital Media &amp; Entertainment Group,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Alibaba,Digital Media &amp; Entertainment Group,Beijing,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017921249","display_name":"Bingren Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingren Yan","raw_affiliation_strings":["Alibaba,Digital Media &amp; Entertainment Group,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Alibaba,Digital Media &amp; Entertainment Group,Beijing,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101406829","display_name":"Zhibo Yang","orcid":"https://orcid.org/0000-0003-2343-7750"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibo Yang","raw_affiliation_strings":["Alibaba,Digital Media &amp; Entertainment Group,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Alibaba,Digital Media &amp; Entertainment Group,Beijing,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101463643","display_name":"Qiang Zhou","orcid":"https://orcid.org/0000-0002-7978-6602"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Zhou","raw_affiliation_strings":["Alibaba,Digital Media &amp; Entertainment Group,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Alibaba,Digital Media &amp; Entertainment Group,Beijing,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015393377","display_name":"Luxi Xing","orcid":"https://orcid.org/0000-0002-5752-2980"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luxi Xing","raw_affiliation_strings":["Alibaba,Digital Media &amp; Entertainment Group,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Alibaba,Digital Media &amp; Entertainment Group,Beijing,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374184","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0003-3870-8744"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Zhang","raw_affiliation_strings":["Alibaba,Digital Media &amp; Entertainment Group,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Alibaba,Digital Media &amp; Entertainment Group,Beijing,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076184681","display_name":"Xingsheng Zhang","orcid":"https://orcid.org/0000-0002-6630-7385"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingsheng Zhang","raw_affiliation_strings":["Alibaba,Digital Media &amp; Entertainment Group,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Alibaba,Digital Media &amp; Entertainment Group,Beijing,China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5034561410"],"corresponding_institution_ids":["https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1941963,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.7509999871253967,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.7509999871253967,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.06279999762773514,"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/T10028","display_name":"Topic Modeling","score":0.05339999869465828,"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/recall","display_name":"Recall","score":0.7926999926567078},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7009999752044678},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5712000131607056},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.4796999990940094},{"id":"https://openalex.org/keywords/spelling","display_name":"Spelling","score":0.41940000653266907},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.35839998722076416},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.34860000014305115}],"concepts":[{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.7926999926567078},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7009999752044678},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5956000089645386},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5716999769210815},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5712000131607056},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.4796999990940094},{"id":"https://openalex.org/C2777801307","wikidata":"https://www.wikidata.org/wiki/Q2088390","display_name":"Spelling","level":2,"score":0.41940000653266907},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.35839998722076416},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.34860000014305115},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.34369999170303345},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C2778757428","wikidata":"https://www.wikidata.org/wiki/Q1250464","display_name":"Realm","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33709999918937683},{"id":"https://openalex.org/C2987098735","wikidata":"https://www.wikidata.org/wiki/Q3808900","display_name":"Recall rate","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.299699991941452},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27570000290870667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":14,"referenced_works":["https://openalex.org/W1494632860","https://openalex.org/W2506719862","https://openalex.org/W2892311186","https://openalex.org/W2952500220","https://openalex.org/W2983735660","https://openalex.org/W3034797320","https://openalex.org/W3035309733","https://openalex.org/W3174595604","https://openalex.org/W4285293661","https://openalex.org/W4296712373","https://openalex.org/W4384156410","https://openalex.org/W4385572215","https://openalex.org/W4387428149","https://openalex.org/W4393160768"],"related_works":[],"abstract_inverted_index":{"In":[0,36],"the":[1,7,18,31,111,128],"realm":[2],"of":[3,34,145],"natural":[4],"language":[5],"processing,":[6],"Chinese":[8],"Spelling":[9],"Correction":[10],"(CSC)":[11],"task":[12],"poses":[13],"a":[14,67,105,142],"significant":[15],"challenge.":[16],"Regrettably,":[17],"progress":[19],"in":[20],"enhancing":[21],"its":[22],"performance":[23],"has":[24],"been":[25],"rather":[26],"restricted,":[27],"mainly":[28],"due":[29],"to":[30,109],"constrained":[32],"incorporation":[33],"knowledge.":[35],"prior":[37],"studies,":[38],"confusion":[39],"sets":[40,49],"were":[41,50],"introduced":[42],"as":[43,59,127],"supplementary":[44],"knowledge":[45,68,121],"sources.":[46],"Nevertheless,":[47],"these":[48],"characterized":[51],"by":[52],"their":[53],"small":[54],"scale":[55],"and":[56,70,165],"merely":[57],"functioned":[58],"ancillary":[60],"features.":[61],"To":[62],"address":[63],"this,":[64],"we":[65,75,93,103],"propose":[66,104],"recall":[69,79,85,95,118],"selection":[71,122],"network":[72,123,156],"(ReSC).":[73],"Initially,":[74],"deployed":[76],"four":[77],"distinct":[78],"methods,":[80],"successfully":[81],"attaining":[82],"an":[83,148],"average":[84],"rate":[86],"exceeding":[87],"93%.":[88],"Notably,":[89],"for":[90],"each":[91],"character,":[92],"can":[94,140],"approximately":[96],"150":[97],"related":[98],"characters":[99,113],"or":[100,114],"words.":[101],"Subsequently,":[102],"Knowledge":[106],"Selection":[107],"Algorithm":[108],"choose":[110],"appropriate":[112],"words":[115],"from":[116,163],"numerous":[117],"sets.":[119],"The":[120],"is":[124],"highly":[125],"efficient,":[126],"F1":[129],"score":[130],"nearly":[131],"reaches":[132],"100%.":[133],"Extensive":[134],"experiments":[135],"have":[136],"proven":[137],"that":[138],"ReSC":[139],"inject":[141],"substantial":[143],"amount":[144],"entities":[146],"with":[147],"even":[149],"lower":[150],"False":[151],"Positive":[152],"Rate.":[153],"This":[154],"novel":[155],"achieves":[157],"better":[158],"results":[159],"across":[160],"six":[161],"datasets":[162],"ECSpell":[164],"SIGHAN.":[166]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
