[1] 李锋刚, 梁钰, GAO X Z, 等基于LDA-wSVM模型的文本分类研究[J]. 计算机应用研究,2015,32(1):21-25.(LI F G,LIANG Y,GAO X Z,et al. Text classification based on LDA-wSVM model[J]. Application Research of Computers,2015,32(1):21-25.) [2] XIE Y,HU X,ZHANG Y,et al. Unsupervised keyword extraction method based on Chinese patent clustering[C]//Proceedings of 2019 IEEE International Conference on Big Knowledge. Piscataway:IEEE,2019:302-309. [3] SHAH F P,PATEL V. A review on feature selection and feature extraction for text classification[C]//Proceedings of 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking. Piscataway:IEEE,2016:2264-2268. [4] DZISEVIČ R,ŠEŠOK D. Text classification using different feature extraction approaches[C]//Proceedings of 2019 Open Conference of Electrical, Electronic and Information Sciences. Piscataway:IEEE,2019:1-4. [5] 周栋, 刘建勋, 王弦, 等. 基于关键词提取的专利在先技术搜索方法研究[J]. 山西大学学报(自然科学版),2014,37(1):34-41.(ZHOU D,LIU J X,WANG X,et al. Research on patent priorart search based on keywords extraction[J]. Journal of Shanxi University(Natural Science Edition),2014,37(1):34-41.) [6] LEI L,QI J,ZHENG K. Patent analytics based on feature vector space model:a case of IoT[J]. IEEE Access,2019,7:45705-45715. [7] LYU L,HAN T. A comparative study of Chinese patent literature automatic classification based on deep learning[C]//Proceedings of 2019 ACM/IEEE Joint Conference on Digital Libraries. Piscataway:IEEE,2019:345-346. [8] REZAUR RAHMAN CHOWDHURY F A,WANG Q,MORENO I L, et al. Attention-based models for text-dependent speaker verification[C]//Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing. Piscataway:IEEE,2018:5359-5363. [9] LI W,GAO S,ZHOU H,et al. The automatic text classification method based on BERT and feature union[C]//Proceedings of the IEEE 25th International Conference on Parallel and Distributed Systems. Piscataway:IEEE,2019:774-777. [10] 江屏, 王川, 孙建广, 等. IPC聚类分析与TRIZ相结合的专利群规避设计方法与应用[J]. 机械工程学报,2015,51(7):144-154. (JIANG P, WANG C, SUN J G, et al. Method and application of patented design around by combination of IPC cluster analysis and TRIZ[J]. Journal of Mechanical Engineering, 2015,51(7):144-154.) [11] MISLAN,HAVILUDDIN,ALFRED R,et al. A Performance neighborhood distance (ndist) between K-Means and SOM algorithms[J]. Advanced Science Letters,2018,24(2):1224-1229. [12] SUN Y,WANG S,LI Y,et al. ERNIE:enhanced representation through knowledge integration[EB/OL].[2020-11-11]. https://arxiv.org/pdf/1904.09223.pdf. [13] KIM Y. Convolutional neural networks for sentence classification[C]//Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing. Stroudsburg,PA:Association for Computational Linguistics,2014:1746-1751. [14] LIU Y,ZHANG J,GAO C,et al. A sensitivity analysis of attention-gated convolutional neural networks for sentence classification[EB/OL].[2020-11-11]. https://arxiv.org/ftp/arxiv/papers/1908/1908.06263.pdf. [15] GOLDBERG Y, LEVY O. Word2Vec explained:deriving Mikolov et al.'s negative-sampling word-embedding method[EB/OL].[2020-11-11]. https://arxiv.org/pdf/1402.3722.pdf. [16] 陈万振, 张予瑶, 苏一丹, 等. 贝叶斯正则化的SOM聚类算法[J]. 计算机工程与设计,2017,38(1):127-131.(CHEN W Z, ZHANG Y Y,SU Y D,et al. SOM clustering algorithm based on Bayesian regularization[J]. Computer Engineering and Design, 2017,38(1):127-131.) [17] 李昌华, 董鑫, 李智杰. 改进的半监督协同SOM图匹配算法[J]. 计算机工程与设计,2019,40(5):1355-1359.(LI C H, DONG X,LI Z J. Improved semi-supervised collaborative SOM graph matching algorithm[J]. Computer Engineering and Design, 2019,40(5):1355-1359.) [18] CHANG W L,PANG L M,TAY K M. Application of selforganizing map to failure modes and effects analysis methodology[J]. Neurocomputing,2017,249:314-320. |