{"id":"https://openalex.org/W7162449149","doi":"https://doi.org/10.15837/ijccc.2026.3.7213","title":"Multi-granularity Curriculum Learning for Chinese Spelling Correction in Legal Texts","display_name":"Multi-granularity Curriculum Learning for Chinese Spelling Correction in Legal Texts","publication_year":2026,"publication_date":"2026-05-26","ids":{"openalex":"https://openalex.org/W7162449149","doi":"https://doi.org/10.15837/ijccc.2026.3.7213"},"language":null,"primary_location":{"id":"doi:10.15837/ijccc.2026.3.7213","is_oa":true,"landing_page_url":"https://doi.org/10.15837/ijccc.2026.3.7213","pdf_url":"https://univagora.ro/jour/index.php/ijccc/article/download/7213/2520","source":{"id":"https://openalex.org/S147751515","display_name":"International Journal of Computers Communications & Control","issn_l":"1841-9836","issn":["1841-9836","1841-9844"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310314650","host_organization_name":"Agora University","host_organization_lineage":["https://openalex.org/P4310314650"],"host_organization_lineage_names":["Agora University"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://univagora.ro/jour/index.php/ijccc/article/download/7213/2520","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137050069","display_name":"Shijin Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shijin Zhou","raw_affiliation_strings":["School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005060223","display_name":"Yabo Liu","orcid":"https://orcid.org/0000-0001-6647-9817"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yabo Liu","raw_affiliation_strings":["School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I184843921"],"apc_list":{"value":500,"currency":"EUR","value_usd":539},"apc_paid":{"value":500,"currency":"EUR","value_usd":539},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.6675964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.3483999967575073,"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/T13629","display_name":"Text Readability and Simplification","score":0.3483999967575073,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.25270000100135803,"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":0.19439999759197235,"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":0.777400016784668},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6970999836921692},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.6298999786376953},{"id":"https://openalex.org/keywords/terminology","display_name":"Terminology","score":0.5857999920845032},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.4652000069618225},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.46480000019073486},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.3986000120639801},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.3790000081062317}],"concepts":[{"id":"https://openalex.org/C2777801307","wikidata":"https://www.wikidata.org/wiki/Q2088390","display_name":"Spelling","level":2,"score":0.777400016784668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772599995136261},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6970999836921692},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.6298999786376953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5899999737739563},{"id":"https://openalex.org/C547195049","wikidata":"https://www.wikidata.org/wiki/Q1725664","display_name":"Terminology","level":2,"score":0.5857999920845032},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5170000195503235},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.4652000069618225},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.46480000019073486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4277999997138977},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C3018824978","wikidata":"https://www.wikidata.org/wiki/Q2894891","display_name":"Error analysis","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C74672266","wikidata":"https://www.wikidata.org/wiki/Q815859","display_name":"Language acquisition","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C2780790391","wikidata":"https://www.wikidata.org/wiki/Q1149626","display_name":"Written language","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.15837/ijccc.2026.3.7213","is_oa":true,"landing_page_url":"https://doi.org/10.15837/ijccc.2026.3.7213","pdf_url":"https://univagora.ro/jour/index.php/ijccc/article/download/7213/2520","source":{"id":"https://openalex.org/S147751515","display_name":"International Journal of Computers Communications & Control","issn_l":"1841-9836","issn":["1841-9836","1841-9844"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310314650","host_organization_name":"Agora University","host_organization_lineage":["https://openalex.org/P4310314650"],"host_organization_lineage_names":["Agora University"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.15837/ijccc.2026.3.7213","is_oa":true,"landing_page_url":"https://doi.org/10.15837/ijccc.2026.3.7213","pdf_url":"https://univagora.ro/jour/index.php/ijccc/article/download/7213/2520","source":{"id":"https://openalex.org/S147751515","display_name":"International Journal of Computers Communications & Control","issn_l":"1841-9836","issn":["1841-9836","1841-9844"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310314650","host_organization_name":"Agora University","host_organization_lineage":["https://openalex.org/P4310314650"],"host_organization_lineage_names":["Agora University"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6750054359436035,"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/W7162449149.pdf","grobid_xml":"https://content.openalex.org/works/W7162449149.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Chinese":[0],"spelling":[1],"correction":[2,83],"(CSC)":[3],"in":[4,62,94],"legal":[5,89,114],"texts":[6],"faces":[7],"unique":[8],"challenges":[9],"due":[10],"to":[11,58,77,148],"specialized":[12],"terminology":[13],"and":[14,37,81,112,138],"complex":[15,60],"error":[16,110],"patterns.":[17],"To":[18,91],"address":[19],"this":[20,95],"gap,":[21],"we":[22,97],"propose":[23],"Multi-granularity":[24],"Curriculum":[25],"Learning":[26],"(mgCL),":[27],"a":[28,101],"novel":[29,102],"two-level":[30],"adaptive":[31],"training":[32,47],"framework":[33],"that":[34],"integrates":[35],"batch-level":[36],"instance-level":[38],"curricula.":[39],"At":[40,68],"the":[41,54,69,118,130,141,154],"batch":[42],"level,":[43,71],"mgCL":[44,72,125],"dynamically":[45],"prioritizes":[46],"samples":[48],"based":[49],"on":[50,84,123,153],"cross-entropy-derived":[51],"difficulty,":[52],"ensuring":[53],"model":[55],"is":[56],"exposed":[57],"increasingly":[59],"examples":[61],"line":[63],"with":[64],"its":[65],"evolving":[66],"competence.":[67],"instance":[70],"leverages":[73],"Monte":[74],"Carlo":[75],"Dropout":[76],"quantify":[78],"prediction":[79],"uncertainty":[80],"focus":[82],"challenging":[85],"characters,":[86],"particularly":[87],"domain-specific":[88],"terms.":[90],"facilitate":[92],"evaluation":[93],"domain,":[96],"also":[98],"introduce":[99],"CNLAW,":[100,124],"benchmark":[103,158],"dataset":[104],"for":[105],"legal-domain":[106],"CSC,":[107],"featuring":[108],"diverse":[109],"patterns":[111],"extensive":[113],"terminology.":[115],"Experiments":[116],"present":[117],"effectiveness":[119],"of":[120],"our":[121],"framework:":[122],"achieves":[126],"98.02%":[127],"F1,":[128],"outperforming":[129],"strong":[131],"Rephrasing":[132],"Language":[133],"Model":[134],"(ReLM)":[135],"baseline":[136],"(96.75%),":[137],"dramatically":[139],"reduces":[140],"False":[142],"Positive":[143],"Rate":[144],"(FPR)":[145],"from":[146],"1.60%":[147],"0.16%.":[149],"Moreover,":[150],"robust":[151],"performance":[152],"widely":[155],"used":[156],"SIGHAN15":[157],"confirms":[159],"mgCL\u2019s":[160],"cross-domain":[161],"generalization.":[162]},"counts_by_year":[],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2026-05-27T00:00:00"}