{"id":"https://openalex.org/W2892311186","doi":"https://doi.org/10.18653/v1/d18-1273","title":"A Hybrid Approach to Automatic Corpus Generation for Chinese Spelling Check","display_name":"A Hybrid Approach to Automatic Corpus Generation for Chinese Spelling Check","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2892311186","doi":"https://doi.org/10.18653/v1/d18-1273","mag":"2892311186"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1273","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1273","pdf_url":"https://www.aclweb.org/anthology/D18-1273.pdf","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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1273.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056754361","display_name":"Dingmin Wang","orcid":"https://orcid.org/0000-0001-9196-2624"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dingmin Wang","raw_affiliation_strings":["Tencent Inc"],"affiliations":[{"raw_affiliation_string":"Tencent Inc","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381758","display_name":"Yan Song","orcid":"https://orcid.org/0000-0002-5668-9068"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Song","raw_affiliation_strings":["Tencent AI Lab"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100336998","display_name":"Jing Li","orcid":"https://orcid.org/0000-0002-8044-2284"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["Tencent AI Lab"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061279074","display_name":"Jialong Han","orcid":"https://orcid.org/0000-0001-5285-9210"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialong Han","raw_affiliation_strings":["Tencent AI Lab"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056317549","display_name":"Haisong Zhang","orcid":"https://orcid.org/0009-0008-0567-3673"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haisong Zhang","raw_affiliation_strings":["Tencent AI Lab"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056754361"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":6.0924,"has_fulltext":true,"cited_by_count":140,"citation_normalized_percentile":{"value":0.97035247,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2517","last_page":"2527"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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":1.0,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9987000226974487,"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/T10028","display_name":"Topic Modeling","score":0.9986000061035156,"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/spelling","display_name":"Spelling","score":0.877966046333313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8597464561462402},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7618249654769897},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7338428497314453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7047895193099976},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6297917366027832},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.4523587226867676},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33537596464157104},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11462834477424622}],"concepts":[{"id":"https://openalex.org/C2777801307","wikidata":"https://www.wikidata.org/wiki/Q2088390","display_name":"Spelling","level":2,"score":0.877966046333313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8597464561462402},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7618249654769897},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7338428497314453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7047895193099976},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6297917366027832},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.4523587226867676},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33537596464157104},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11462834477424622},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1273","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1273","pdf_url":"https://www.aclweb.org/anthology/D18-1273.pdf","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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1273","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1273","pdf_url":"https://www.aclweb.org/anthology/D18-1273.pdf","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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8799999952316284,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2892311186.pdf","grobid_xml":"https://content.openalex.org/works/W2892311186.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W99399284","https://openalex.org/W1494632860","https://openalex.org/W1508165687","https://openalex.org/W1524333225","https://openalex.org/W1556663161","https://openalex.org/W1601624250","https://openalex.org/W1741907867","https://openalex.org/W1810943226","https://openalex.org/W1981533728","https://openalex.org/W2001642682","https://openalex.org/W2016195898","https://openalex.org/W2070944431","https://openalex.org/W2079735306","https://openalex.org/W2092510119","https://openalex.org/W2099143268","https://openalex.org/W2110903505","https://openalex.org/W2110974939","https://openalex.org/W2113045821","https://openalex.org/W2127610924","https://openalex.org/W2157951638","https://openalex.org/W2159406587","https://openalex.org/W2163377725","https://openalex.org/W2165945467","https://openalex.org/W2200986169","https://openalex.org/W2210443512","https://openalex.org/W2250444785","https://openalex.org/W2250680451","https://openalex.org/W2250952509","https://openalex.org/W2250990886","https://openalex.org/W2251157340","https://openalex.org/W2251568283","https://openalex.org/W2251584595","https://openalex.org/W2251629135","https://openalex.org/W2251703655","https://openalex.org/W2251873470","https://openalex.org/W2579704464","https://openalex.org/W2785643982","https://openalex.org/W2787190016","https://openalex.org/W2787402609","https://openalex.org/W2963242190","https://openalex.org/W3145501851","https://openalex.org/W3210232381"],"related_works":["https://openalex.org/W2161008081","https://openalex.org/W4298186509","https://openalex.org/W2556702969","https://openalex.org/W217221262","https://openalex.org/W611030372","https://openalex.org/W1974418053","https://openalex.org/W2021532426","https://openalex.org/W2530486443","https://openalex.org/W2081317458","https://openalex.org/W2228086542"],"abstract_inverted_index":{"Chinese":[0],"spelling":[1,76],"check":[2],"(CSC)":[3],"is":[4,45],"a":[5,15,66],"challenging":[6],"yet":[7],"meaningful":[8],"task,":[9],"which":[10,78],"not":[11,53],"only":[12],"serves":[13],"as":[14],"preprocessing":[16],"in":[17,33,55,136],"many":[18],"natural":[19],"language":[20],"processing":[21],"(NLP)":[22],"applications,":[23],"but":[24],"also":[25],"facilitates":[26],"reading":[27],"and":[28,58,101],"understanding":[29],"of":[30,69,117,124],"running":[31],"texts":[32],"peoples'":[34],"daily":[35],"lives.":[36],"However,":[37],"to":[38,87,107],"utilize":[39],"datadriven":[40],"approaches":[41],"for":[42,103],"CSC,":[43],"there":[44],"one":[46],"major":[47],"limitation":[48],"that":[49],"annotated":[50],"corpora":[51],"are":[52,79,99],"enough":[54],"applying":[56],"algorithms":[57],"building":[59],"models.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"propose":[65],"novel":[67],"approach":[68],"constructing":[70],"CSC":[71,104],"corpus":[72],"with":[73,105],"automatically":[74],"generated":[75],"errors,":[77],"either":[80],"visually":[81],"or":[82],"phonologically":[83],"resembled":[84],"characters,":[85],"corresponding":[86],"the":[88,94,115,118,122],"OCRand":[89],"ASR-based":[90],"methods,":[91],"respectively.":[92],"Upon":[93],"constructed":[95],"corpus,":[96,119],"different":[97],"models":[98],"trained":[100],"evaluated":[102],"respect":[106],"three":[108],"standard":[109],"test":[110],"sets.":[111],"Experimental":[112],"results":[113],"demonstrate":[114],"effectiveness":[116],"therefore":[120],"confirm":[121],"validity":[123],"our":[125],"approach.":[126],"*":[127],"This":[128],"work":[129],"was":[130],"conducted":[131],"during":[132],"Dingmin":[133],"Wang's":[134],"internship":[135],"Tencent":[137],"AI":[138],"Lab.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":7}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}