{"id":"https://openalex.org/W2955906716","doi":"https://doi.org/10.18653/v1/w18-3403","title":"Multi-task learning for historical text normalization: Size matters","display_name":"Multi-task learning for historical text normalization: Size matters","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2955906716","doi":"https://doi.org/10.18653/v1/w18-3403","mag":"2955906716"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w18-3403","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-3403","pdf_url":"https://www.aclweb.org/anthology/W18-3403.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 Workshop on Deep Learning Approaches for Low-Resource NLP","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W18-3403.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005438563","display_name":"Marcel Bollmann","orcid":"https://orcid.org/0000-0003-2598-8150"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Marcel Bollmann","raw_affiliation_strings":["Dept. of Computer Science University of Copenhagen Denmark"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science University of Copenhagen Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018138946","display_name":"Anders S\u00f8gaard","orcid":"https://orcid.org/0000-0001-5250-4276"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Anders S\u00f8gaard","raw_affiliation_strings":["Dept. of Computer Science University of Copenhagen Denmark"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science University of Copenhagen Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028729586","display_name":"Joachim Bingel","orcid":"https://orcid.org/0000-0002-4113-3390"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Joachim Bingel","raw_affiliation_strings":["Dept. of Computer Science University of Copenhagen Denmark"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science University of Copenhagen Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5005438563"],"corresponding_institution_ids":["https://openalex.org/I124055696"],"apc_list":null,"apc_paid":null,"fwci":2.0309,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.90241785,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9994000196456909,"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":0.989300012588501,"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/computer-science","display_name":"Computer science","score":0.7142854332923889},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.686706006526947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5094655156135559},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.483532190322876},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4656912088394165},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09126722812652588},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.08109065890312195},{"id":"https://openalex.org/keywords/social-science","display_name":"Social science","score":0.07286158204078674}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7142854332923889},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.686706006526947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5094655156135559},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.483532190322876},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4656912088394165},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09126722812652588},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.08109065890312195},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.07286158204078674},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/w18-3403","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-3403","pdf_url":"https://www.aclweb.org/anthology/W18-3403.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 Workshop on Deep Learning Approaches for Low-Resource NLP","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/e0c40b1c-1f9d-4427-9d28-902cceaad388","is_oa":false,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/e0c40b1c-1f9d-4427-9d28-902cceaad388","pdf_url":null,"source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Bollmann , M M , S\u00f8gaard , A & Bingel , J 2018 , Multi-task learning for historical text normalization : Size matters . in Proceedings of the Workshop on Deep Learning Approaches for Low-Resource NLP . Association for Computational Linguistics , pp. 19\u201324 , Workshop on Deep Learning Approaches for Low-Resource NLP , Melbourne , Australia , 19/07/2018 .","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"doi:10.18653/v1/w18-3403","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-3403","pdf_url":"https://www.aclweb.org/anthology/W18-3403.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 Workshop on Deep Learning Approaches for Low-Resource NLP","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G5106512922","display_name":null,"funder_award_id":"Deutsche Forschungsgemeinschaft (DFG","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G6024419964","display_name":null,"funder_award_id":"Deutsche Forschungsgemeinschaft (DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G6052429835","display_name":null,"funder_award_id":"(DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320323715","display_name":"Ruhr-Universit\u00e4t Bochum","ror":"https://ror.org/04tsk2644"},{"id":"https://openalex.org/F4320324424","display_name":"TrygFonden","ror":"https://ror.org/02rcazp29"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2955906716.pdf","grobid_xml":"https://content.openalex.org/works/W2955906716.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2124725212","https://openalex.org/W2146867136","https://openalex.org/W2251743902","https://openalex.org/W2266080033","https://openalex.org/W2557768656","https://openalex.org/W2592170186","https://openalex.org/W2741138687","https://openalex.org/W2896234464","https://openalex.org/W2949369097","https://openalex.org/W2963842982","https://openalex.org/W2963988211","https://openalex.org/W2964121744","https://openalex.org/W2982630078","https://openalex.org/W4293543602"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W4294432981","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Historical":[0],"text":[1,67],"normalization":[2,68],"suffers":[3],"from":[4,25,42,70],"small":[5],"datasets":[6,41],"that":[7,16,101],"exhibit":[8],"high":[9],"variance,":[10],"and":[11,46,51,87],"previous":[12],"work":[13,36],"has":[14,37,94],"shown":[15],"multitask":[17],"learning":[18,79,103],"can":[19],"be":[20],"used":[21],"to":[22,30,40,92],"leverage":[23],"data":[24,109],"related":[26],"problems":[27],"in":[28],"order":[29],"obtain":[31],"more":[32],"robust":[33],"models.":[34],"Previous":[35],"been":[38,95],"limited":[39],"a":[43,47],"specific":[44,48],"language":[45],"historical":[49,66],"period,":[50],"it":[52],"is":[53,110],"not":[54],"clear":[55],"whether":[56],"results":[57],"generalize.":[58],"It":[59],"therefore":[60],"remains":[61],"an":[62],"open":[63],"problem,":[64],"when":[65,106],"benefits":[69,76],"multi-task":[71,78,102],"learning.":[72],"We":[73],"explore":[74],"the":[75],"of":[77],"across":[80],"10":[81],"different":[82,85],"datasets,":[83],"representing":[84],"languages":[86],"periods.":[88],"Our":[89],"main":[90],"findingcontrary":[91],"what":[93],"observed":[96],"for":[97],"other":[98],"NLP":[99],"tasks-is":[100],"mainly":[104],"works":[105],"target":[107],"task":[108],"very":[111],"scarce.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":9}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}