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Разработка автоматизированных методов порождения служебных документов на естественном языке
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| dc.contributor.author | Пальчунов, Дмитрий Евгеньевич | ru_RU |
| dc.contributor.author | Финк, Артём Альбертович | ru_RU |
| dc.contributor.author | Palchunov, D. E. | en |
| dc.contributor.author | Fink, A. A. | en |
| dc.creator | Новосибирский государственный университет | ru-Ru |
| dc.creator | Институт математики им. С. Л. Соболева СО РАН | ru-Ru |
| dc.creator | Novosibirsk State University | en |
| dc.creator | Institute of Mathematics SB RAS | en |
| dc.date.accessioned | 2017-10-02T13:17:34Z | |
| dc.date.available | 2017-10-02T13:17:34Z | |
| dc.date.issued | 2017-09 | |
| dc.identifier.citation | Пальчунов Д. Е., Финк А. А. Разработка автоматизированных методов порождения служебных документов на естественном языке // Вестн. НГУ. Серия: Информационные технологии. 2017. Т. 15, № 3. С. 79–89. DOI 10.25205/1818-7900-2017-15-3-79-89. ISSN 1818-7900. | ru-Ru |
| dc.identifier.citation | Palchunov D. E., Fink A. A. The Development of Automated Methods of Generation of Official Documents in Natural Language. Vestnik NSU. Series: Information Technologies, 2017, vol. 15, no. 3, p. 79–89. DOI 10.25205/1818-7900-2017-15-3-79-89. ISSN 1818-7900. (In Russ.) | en |
| dc.identifier.issn | 1818-7900 | |
| dc.identifier.other | DOI 10.25205/1818-7900-2017-15-3-79-89 | |
| dc.identifier.uri | https://lib.nsu.ru/xmlui/handle/nsu/13449 | |
| dc.description.abstract | Статья посвящена проблеме автоматизированного порождения служебных документов на естественном языке с логическим контролем их правильности. Рассмотрены существующие подходы к автоматизации порождения документов. Предложен метод автоматизированного порождения логически правильных документов на естественном языке, основанный на применении параметрических шаблонов. | ru_RU |
| dc.description.abstract | The paper is devoted to the problem of automated generation of official documents in natural language with logical control of their correctness. Existing approaches to automation of document generation are considered. We present a method of automated generation of logically correct documents in natural language based on the use of parametric templates. | en |
| dc.language.iso | ru | ru_RU |
| dc.publisher | Новосибирский государственный университет | ru_RU |
| dc.subject | извлечение знаний | ru_RU |
| dc.subject | представление знаний | ru_RU |
| dc.subject | нормативные документы | ru_RU |
| dc.subject | служебные документы | ru_RU |
| dc.subject | параметрические шаблоны | ru_RU |
| dc.subject | knowledge extraction | en |
| dc.subject | knowledge representation | en |
| dc.subject | regulatory documents | en |
| dc.subject | official documents | en |
| dc.subject | parametric templates | en |
| dc.title | Разработка автоматизированных методов порождения служебных документов на естественном языке | ru_RU |
| dc.title.alternative | The Development of Automated Methods of Generation of Official Documents in Natural Language | en |
| dc.type | Article | ru_RU |
| dc.description.reference | 1. Деревянко Д. В., Пальчунов Д. Е. Формальные методы разработки вопросно-ответной системы на естественном языке // Вестн. Новосиб. гос. ун-та. Серия: Информационные технологии. 2014. Т. 12, вып. 3. С. 34 –47. 2. Wu F., Weld D. S. Automatically refining the wikipedia infobox ontology // Proc. of the 17th InternationalConference on World Wide Web, WWW. ACM, 2008. Р. 635–644. 3. Lehmann J., Isele R., Jakob M., Jentzsch A., Kontokostas D., Mendes P. N., Hellmann S., Morsey M., Kleef P. van, Auer S., Bizer C. DBpedia – A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia // Semantic Web Journal. 2015. Vol. 6, iss. 2. P. 167–195. 4. Sirin E., Parsia B. SPARQL-DL: SPARQL query for OWL-DL // Third OWL Experiences and Directions Workshop (OWLED). 2007. 5. Palchunov D., Yakhyaeva G., Yasinskaya O. Software system for the diagnosis of thae spine diseases using case-based reasoning // Proc. of the International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON / SibMedInfo – 2015). Novosibirsk, 2015. P. 150–155. 6. Naydanov Ch., Palchunov D., Sazonova P. Development of automated methods for the prevention of risks of critical conditions, based on the analysis of the knowledge extracted from the medical histories // Сиб. науч. мед. журн. 2016. Т. 36, вып. 1. С. 105–113. 7. Palchunov D., Yakhyaeva G., Dolgusheva E. Conceptual Methods for Identifying Needs of Mobile Network Subscribers // Proc. of the 13th International Conference on Concept Lattices and Their Applications. Moscow, 2016. Р. 147–160. 8. Motik B., Shearer R., Horrocks I. Hypertableau reasoning for description logics // Journal of Artificial Intelligence Research. 2009. No. 36. P. 165–228. 9. Сокирко А. В. Семантические словари в автоматической обработке текста (по материалам системы ДИАЛИНГ): Дис. … д-ра техн. наук. М., 2001. 120 с. 10. Леонтьева Н. Н. Русский общесемантический словарь (РОСС): структура, наполнение // НТИ. Сер. 2. 1997. № 12. С. 5–20. | ru-Ru |
| dc.description.reference | 1. Derevyanko D. V., Palchunov D. E. Formal methods of development of the questionanswering system on natural language. Vestnik NSU. Series: Information Technologies, 2014, vol. 12, no. 3, p. 34–47. (In Russ.) 2. Wu F., Weld D. S. Automatically refining the wikipedia infobox ontology. Proc. of the 17th InternationalConference on World Wide Web, WWW. ACM, 2008, p. 635–644. 3. Lehmann J., Isele R., Jakob M., Jentzsch A., Kontokostas D., Mendes P. N., Hellmann S. Morsey M., Kleef P. van, Auer S., Bizer C. DBpedia – A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia. Semantic Web Journal, 2015, vol. 6, iss. 2, p. 167–195. 4. Sirin E., Parsia B. SPARQL-DL: SPARQL query for OWL-DL. Third OWL Experiences and Directions Workshop (OWLED), 2007. 5. Palchunov D., Yakhyaeva G., Yasinskaya O. Software system for the diagnosis of thae spine diseases using case-based reasoning. Proc. of the International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON / SibMedInfo – 2015). Novosibirsk, 2015, p. 150–155. 6. Naydanov Ch., Palchunov D., Sazonova P. Development of automated methods for the prevention of risks of critical conditions, based on the analysis of the knowledge extracted from the medical histories. Siberian Scientific Medical Journal, 2016, vol. 36, iss. 1, p. 105–113. 7. Palchunov D., Yakhyaeva G., Dolgusheva E. Conceptual Methods for Identifying Needs of Mobile Network Subscribers. Proc. of the 13th International Conference on Concept Lattices and Their Applications. Moscow, 2016, р. 147–160. 8. Motik B., Shearer R., Horrocks I. Hypertableau reasoning for description logics. Journal of Artificial Intelligence Research, 2009, no. 36, p. 165–228. 9. Sokirko A. V. Semantic dictionaries in automatic text parsing (On materials of the system DIALING): Dissertation of Doctor of Technical Sciences. Moscow, 2001, 120 p. (In Russ.) 10. Leonteva N. N. Russian all-semantic dictionary (ROSS): structure, filling. NTI. Series 2, 1997, no. 12, p. 5–20. (In Russ.) | en |
| dc.subject.udc | 004.825 | |
| dc.relation.ispartofvolume | 15 | |
| dc.relation.ispartofnumber | 3 | |
| dc.relation.ispartofpages | 79–89 |
