{"id":"https://openalex.org/W2988673764","doi":"https://doi.org/10.18653/v1/d19-5821","title":"A Recurrent BERT-based Model for Question Generation","display_name":"A Recurrent BERT-based Model for Question Generation","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2988673764","doi":"https://doi.org/10.18653/v1/d19-5821","mag":"2988673764"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d19-5821","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-5821","pdf_url":null,"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 2nd Workshop on Machine Reading for Question Answering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/d19-5821","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050477890","display_name":"Ying-Hong Chan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ying-Hong Chan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5024883783","display_name":"Yao-Chung Fan","orcid":"https://orcid.org/0000-0002-6894-015X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao-Chung Fan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050477890"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.7057,"has_fulltext":false,"cited_by_count":157,"citation_normalized_percentile":{"value":0.98771742,"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":"154","last_page":"162"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9991999864578247,"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/T12031","display_name":"Speech and dialogue systems","score":0.9700999855995178,"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/language-model","display_name":"Language model","score":0.8421581983566284},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8377026319503784},{"id":"https://openalex.org/keywords/restructuring","display_name":"Restructuring","score":0.6678600907325745},{"id":"https://openalex.org/keywords/text-generation","display_name":"Text generation","score":0.6586064100265503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6191850304603577},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5309747457504272},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5170496106147766},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4238564670085907},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37450963258743286},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.157636821269989}],"concepts":[{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.8421581983566284},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8377026319503784},{"id":"https://openalex.org/C45237549","wikidata":"https://www.wikidata.org/wiki/Q1376796","display_name":"Restructuring","level":2,"score":0.6678600907325745},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.6586064100265503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6191850304603577},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5309747457504272},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5170496106147766},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4238564670085907},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37450963258743286},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.157636821269989},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d19-5821","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-5821","pdf_url":null,"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 2nd Workshop on Machine Reading for Question Answering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d19-5821","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-5821","pdf_url":null,"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 2nd Workshop on Machine Reading for Question Answering","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1531374185","https://openalex.org/W1555380324","https://openalex.org/W1902237438","https://openalex.org/W1924770834","https://openalex.org/W2064675550","https://openalex.org/W2072385577","https://openalex.org/W2101105183","https://openalex.org/W2130942839","https://openalex.org/W2133459682","https://openalex.org/W2151466713","https://openalex.org/W2154652894","https://openalex.org/W2250425483","https://openalex.org/W2606333299","https://openalex.org/W2610891036","https://openalex.org/W2622069672","https://openalex.org/W2624022918","https://openalex.org/W2729046720","https://openalex.org/W2753613501","https://openalex.org/W2757978590","https://openalex.org/W2890166583","https://openalex.org/W2962717047","https://openalex.org/W2962970841","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963748441"],"related_works":["https://openalex.org/W3204607391","https://openalex.org/W2964413124","https://openalex.org/W4388937922","https://openalex.org/W3113264705","https://openalex.org/W2988673764","https://openalex.org/W2996388263","https://openalex.org/W2122804826","https://openalex.org/W2138640103","https://openalex.org/W2986367395","https://openalex.org/W4388685619"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3,52],"investigate":[4],"the":[5,8,42,80,97,102],"employment":[6,61],"of":[7,26,44,101],"pre-trained":[9],"BERT":[10,27,38,47,60],"language":[11],"model":[12,91],"to":[13,108],"tackle":[14],"question":[15,29],"generation":[16,30],"tasks.":[17,31],"We":[18],"introduce":[19],"three":[20],"neural":[21],"architectures":[22],"built":[23],"on":[24,79],"top":[25],"for":[28,48,66],"The":[32],"first":[33],"one":[34],"is":[35],"a":[36,63],"straightforward":[37],"employment,":[39],"which":[40,95],"reveals":[41],"defects":[43],"directly":[45],"using":[46],"text":[49],"generation.":[50],"Accordingly,":[51],"propose":[53],"another":[54],"two":[55],"models":[56,74,105],"by":[57],"restructuring":[58],"our":[59,89],"into":[62],"sequential":[64],"manner":[65],"taking":[67],"information":[68],"from":[69,106],"previous":[70],"decoded":[71],"results.":[72],"Our":[73],"are":[75],"trained":[76],"and":[77],"evaluated":[78],"recent":[81],"question-answering":[82],"dataset":[83],"SQuAD.":[84],"Experiment":[85],"results":[86],"show":[87],"that":[88],"best":[90,104],"yields":[92],"state-of-the-art":[93],"performance":[94],"advances":[96],"BLEU":[98],"4":[99],"score":[100],"existing":[103],"16.85":[107],"22.17.":[109]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":44},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":11}],"updated_date":"2026-04-20T07:46:08.049788","created_date":"2025-10-10T00:00:00"}