乐胖代购免代理版

{"id":"https://openalex.org/W4205616177","doi":"https://doi.org/10.1109/bigdata52589.2021.9671471","title":"Deep Sentence Denoising beyond Grammatical Error Correction","display_name":"Deep Sentence Denoising beyond Grammatical Error Correction","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205616177","doi":"https://doi.org/10.1109/bigdata52589.2021.9671471"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671471","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5027483927","display_name":"Zhantong Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhantong Liang","raw_affiliation_strings":["Department of Computer Science, The George Washington Univerisity, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The George Washington Univerisity, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111635384","display_name":"Abdou Youssef","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdou Youssef","raw_affiliation_strings":["Department of Computer Science, The George Washington Univerisity, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The George Washington Univerisity, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":57},"biblio":{"volume":null,"issue":null,"first_page":"1686","last_page":"1691"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9999,"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":0.9999,"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":0.9995,"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":0.9995,"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/vagueness","display_name":"Vagueness","score":0.50855196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7729537},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6690526},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.62169814},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5953384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.53252697},{"id":"https://openalex.org/C2776825360","wikidata":"https://www.wikidata.org/wiki/Q1411921","display_name":"Vagueness","level":3,"score":0.50855196},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.50555205},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.49623734},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49200413},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.48429838},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.43700328},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.42317587},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.19818553},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1739577},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16985694},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671471","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.75,"display_name":"Quality education"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":20,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2081580037","https://openalex.org/W2098297786","https://openalex.org/W2170240176","https://openalex.org/W2170527467","https://openalex.org/W2183341477","https://openalex.org/W2594978815","https://openalex.org/W2740839465","https://openalex.org/W2810035278","https://openalex.org/W2933138175","https://openalex.org/W2936597270","https://openalex.org/W2963881719","https://openalex.org/W2964223283","https://openalex.org/W2970294904","https://openalex.org/W2970429618","https://openalex.org/W2970521905","https://openalex.org/W2971296908","https://openalex.org/W3037162118","https://openalex.org/W4293569541","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4213284915","https://openalex.org/W4212798463","https://openalex.org/W3160820793","https://openalex.org/W2974127468","https://openalex.org/W2964061033","https://openalex.org/W2501465302","https://openalex.org/W2496023037","https://openalex.org/W2486940251","https://openalex.org/W2350451705","https://openalex.org/W2276167089"],"abstract_inverted_index":{"Clear":[0],"and":[1,12,39,49,55,60,91,99],"efficient":[2,104],"communication":[3],"requires":[4],"more":[5],"than":[6],"grammatical":[7],"correctness":[8],"to":[9,28,79],"ensure":[10],"fluency":[11],"semantic":[13],"correctness,":[14],"especially":[15],"for":[16,85,94,109],"non-native":[17],"speakers.":[18],"Thus,":[19],"we":[20],"propose":[21],"a":[22,37],"new":[23],"task":[24],"\u2013":[25],"Sentence":[26],"Denoising,":[27],"go":[29],"beyond":[30],"Grammatical":[31],"Error":[32],"Correction":[33],"(GEC).":[34],"We":[35,57,88],"define":[36],"rich":[38],"linguistics-inspired":[40],"noise":[41,65,82,98],"taxonomy":[42],"consisting":[43],"of":[44,47,64,67,112],"13":[45,69],"types":[46,63],"noise,":[48],"categorize":[50],"them":[51,90],"into":[52,83],"vagueness,":[53],"redundancy,":[54],"incoherence.":[56],"then":[58],"generate":[59],"study":[61],"4":[62],"out":[66],"the":[68],"because":[70],"they":[71],"serve":[72],"as":[73],"building":[74,86],"blocks.":[75],"Methods":[76],"are":[77],"proposed":[78],"inject":[80],"targeted":[81],"sentences":[84],"datasets.":[87],"publish":[89],"give":[92],"benchmarks":[93],"denoising":[95,110],"both":[96],"individual":[97],"compound":[100],"noise.":[101,113],"Finally,":[102],"an":[103],"training":[105],"approach":[106],"is":[107],"designed":[108],"combinations":[111]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4205616177","counts_by_year":[],"updated_date":"2024-12-09T11:22:01.967286","created_date":"2022-01-25"}