[1] |
董振东, 董强. 知网[Z/OL].[2021-05-07]. http://www.keenage.com/zhiwang/c_zhiwang.html.
|
[2] |
BLOOMFIELD L. A set of postulates for the science of language[J]. Language, 1926,2(3):153-164.
doi: 10.2307/408741
URL
|
[3] |
LIU Q, LI S J. Word similarity computing based on how-net[J]. CLCLP, 2002,7(2):59-76.
|
[4] |
FU X H, GUO L, GAO Y Y, et al. Multi-aspect sentiment analysis for chinese online social reviews based on topic modeling and hownet lexicon[J]. Knowledge-Based Systems, 2013,37(2):186-195.
doi: 10.1016/j.knosys.2012.08.003
URL
|
[5] |
NIU Y L, XIE R B, YUAN X C, et al. Improved word representation learning with sememes[C]// Association of Computational Linguistics.Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017: 2049-2058.
|
[6] |
XIE R B, YUAN X C, LIU Z Y, et al. Lexical sememe prediction via word embeddings and matrix factorization[C]// International Joint Conferences on Artificial Intelligence Organization.Proceeding of the 26th International Joint Conference on Artificial Intelligence, 2017: 4200-4206.
|
[7] |
GU Y H, YAN J, ZHU H, et al. Language modeling with sparse product of sememe experts[C]// Association for Computational Linguistics.Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018: 4642-4651.
|
[8] |
QI F C, YANG C H, LIU Z Y, et al. Openhownet: An open sememe-based lexical knowledge base[J/OL] .[2021-05-07]. CoRR,abs/1901.09957. 2019.
|
[9] |
CHEN K J, HUANG S L, SHIH Y Y, et al. Extended-HowNet: A representational framework for concepts[C]// Asian Federation of Natural Language Processing.Proceedings of OntoLex 2005-Ontologies and Lexical Resources, 2005.
|
[10] |
SHIH Y Y, MA W Y . Extended hownet 2.0-an entity-relation common-sense representation model[C]// European Language Resources Association. Proceeding of the 11th International Conference on Language Resources and Evaluation Conference, 2018.
|
[11] |
王莹莹, 白宇, 丁长林, 等. 面向语义检索的中医理论知识库构建方法的研究[J]. 中文信息学报, 2012,26(5):72-78.
|
[12] |
张桂平, 刁丽娜, 王裴岩. 基于HowNet的航空术语语义知识库的构建[J]. 中文信息学报, 2014,28(5):92-101.
|
[13] |
王羊羊, 陈刚, 蔡东风, 等. 基于HowNet的术语语义知识库构建技术[J]. 沈阳航空航天大学学报, 2016,33(4):78-84.
|
[14] |
MIKOLOV T, CORRADO G, CHEN K, et al. Efficient Estimation of Word Representations in Vector Space[C]// Proceedings of the 1st International Conference on Learning Representations, 2013.
|
[15] |
《中国航空百科词典》编辑部. 中国航空百科词典[M]. 北京: 航空工业出版社, 2000.
|
[16] |
KDML:知网知识系统描述语言[Z/OL].[2021-05-07]. http://www.keenage.com/TheoryandpracticeofHowNet/07.pdf.
|
[17] |
COHEN J. A coefficient of agreement for nominal scales[J]. Educational & Psychological Measurement, 1960,20(1):37-46.
|
[18] |
STUDENT. Probable error of a correlation coefficient[J]. Biometrika, 1908,6(2/3):302-310.
doi: 10.1093/biomet/6.2-3.302
URL
|
[19] |
XIA T. Study on chinese words semantic similarity computation[J]. Computer Engineering, 2007,33(6):191-194.
doi: 10.1007/s00366-016-0464-z
URL
|
[20] |
NIU Y L, XIE R B, YUAN X C, et al. Improved word representation learning with sememes[C]// Association for Computational Linguistics. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017: 2049-2058.
|
[21] |
DEVLIN J, CHANG M W, LEE K, et al. BERT: Pre-training of deep bidirectional transformers for language understanding[C]// Association for Computational Linguistics.Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies, 2019: 4171-4186.
|
[22] |
SONG Y, SHI S M, LI J, et al. Directional skip-gram: Explicitly distinguishing left and right context for word embeddings[C]// Association for Computational Linguistics.Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,NAACL-HLT, 2018: 175-180.
|