Journal of Library and Information Science in Agriculture ›› 2022, Vol. 34 ›› Issue (4): 63-73.doi: 10.13998/j.cnki.issn1002-1248.21-0382
Previous Articles Next Articles
LI Bo, LI Honglian, GUAN Qing, LIU Yang
CLC Number:
| [1] 柳益君, 何胜, 吴智勤, 等. 基于用户社交网络分析的高校图书馆主题多样性阅读推荐[J]. 图书情报工作, 2018, 62(8): 67-73. LIU Y J, HE S, WU Z Q, et al.Reading recommendation with subject diversity of university libraries based on analysis of user social network[J]. Library and information service, 2018, 62(8): 67-73. [2] MARZ N, WARREN J.Big data: Principles and best practices of scalable real time data systems[M]. Manning publications co, 2015. [3] 王晰巍, 贾若男, 王铎, 等. 图书情报领域人工智能的研究热点及发展趋势研究[J]. 图书情报工作, 2019, 63(1): 70-80. WANG X W, JIA R N, WANG D, et al.Research on the development trend of artificial intelligence research in library and information field[J]. Library and information service, 2019, 63(1): 70-80. [4] MOHEY D. A survey on sentiment analysis challenges[EB/OL]. [2016-04-26].http://www.sciencedirect.com/science/arti-cle/pii/S10 18363916300071. [5] 唐晓波, 刘广超. 细粒度情感分析研究综述[J]. 图书情报工作, 2017, 61(5): 132-140. TANG X B, LIU G C.Research review on fine-grained sentiment analysis[J]. Library and information service, 2017, 61(5): 132-140. [6] PANG B, LEE L, VAITHYANTHAN S.Thumbs up: Sentiment clas-sification using machine learning techniques[C]. Proceedings of the conference on empirical methods in natural language processing, Stroudsburg, USA, 2002: 79-86. [7] BARBOSA L, FENG J.Robust sentiment detection on twitter from biased and noisy data[C]. International conference on computational linguistics: Posters, association for computational linguistic, 2010: 36-44. [8] 张文亮, 付枭男, 王彦芳. 我国省级公共图书馆评价研究——以大众点评网数据为例[J]. 图书情报工作, 2019, 63(5): 51-60. ZAHNG W L, FU X N, WANG Y F.Research on evaluation of provincial public library - Taking dianping.com data as an example[J]. Library and information service, 2019, 63(5): 51-60. [9] 毕达天, 王福. 移动图书馆场景化信息接受过程的情感变化研究[J]. 图书情报工作, 2019, 63(6): 20-28. BI D T, WANG F.Emotional changes in scenario acceptance process of mobile library[J]. Library and information service, 2019, 63(6): 20-28. [10] 曾子明, 杨倩雯. 基于LDA和AdaBoost多特征组合的微博情感分析[J]. 数据分析与知识发现, 2018, 2(8): 51-59. ZENG Z M, YANG Q W.Sentiment analysis for micro-blogs with LDA and AdaBoost[J]. Data analysis and knowledge discovery, 2018, 2(8): 51-59. [11] KALCHBRENNER N, GREFENSTETTE E, BLUNSOM P.A convolutional neural network for modelling sentences[J]. EprintArxiv, 2014, 1. [12] KIM Y.Convolutional neural networks for sentence classification[J]. EprintArxiv, 2014. [13] BENGIO Y, DUCHARME R, VINCENT P, et al.A neural probabilistic language model[J]. Journal of machine learning research, 2003, 3: 1137-1155. [14] 周锦峰, 叶施仁, 王晖. 卷积神经网络在短文本情感多分类标注应用[J]. 计算机工程与应用, 2018, 54(22): 133-138, 149. ZHOU J F, YE S R, WANG H.Application of convolutional neural network in multi-category classification for short text sentiment[J]. Computer engineering and applications, 2018, 54(22): 133-138, 149. [15] HAI H D, PWC P, ANGELIKA M, et al.Deep learning for Aspect- Based sentiment analysis: A comparative review[J]. Expert systems with applications, 2019(118): 272-299. [16] HUYTIEN N, MINH L N.An ensemble method with sentiment features and clustering support[J]. Neurocomputing, 2019(370): 155-165. [17] HOON-KENG P, WUN-SHE Y, YEE-KAI T, et al.Hierarchical gated recurrent neural network with adversarial and virtual adversarial training on text classification[J]. Neural networks, 2019(119): 299-312. [18] NIKHIL P, MANISH G, PONNURANGAM K, et al. A distant supervision based approach to medical persona classification[J]. Journal of biomedical informatics, 2019(94). [19] SU C, LI J C, PENG Y, et al.Chinese metaphor sentiment computing via considering culture[J]. Neurocomputing, 2019(352): 33-41. [20] HINTON G E.Learning distributed representations of concepts[C]. Eighth conference of the cognitive science society, 1989. [21] WANG Y, HUANG M, ZHU X, et al.Attention-based LSTM for aspect-level sentiment classification[C]. Conference on empirical methods in natural language processing, 2017: 606-615. [22] 余本功, 张培行, 许庆堂. 基于F-BiGRU情感分析的产品选择方法[J]. 数据分析与知识发现, 2018, 2(9): 22-30. YU B G, ZHANG P H, XU Q T.Selecting products based on F-BiGRU sentiment analysis[J]. Data analysis and knowledge discovery, 2018, 2(9): 22-30. [23] 胡荣磊, 芮璐, 齐筱, 等. 基于循环神经网络和注意力模型的文本情感分析[J]. 计算机应用研究, 2019, 36(11): 3282-3285. HU R L, RUI L, QI X, et al.Text sentiment analysis based on recurrent neural networks and attention model[J]. Application research of computers, 2019, 36(11): 3282-3285. [24] 郝志峰, 黄浩, 蔡瑞初, 等. 基于多特征融合与双向RNN的细粒度意见分析[J]. 计算机工程, 2018, 44(7): 199-204, 211. HAO Z F, HUANG H, CAI R C, et al.Fine-grained opinion analysis based on multi-feature fusion and bidirectional RNN[J]. Computer engineering, 2018, 44(7): 199-204, 211. [25] BAHDANAU D, CHO K, BENGIO Y.Neural machine translation by jointly learning to align and translate[J]. ArXiv preprint arxiv, 2014: 1409-1473. [26] SCHUSTER M, PALIWAL K K.Bidirectional recurrent neural networks[J]. IEEE transactions on signal processing, 1997, 45(11): 2673-2681. [27] MNIH V, HEESS N, GRAVES A, et al.Recurrent models of visual attention[C]. Advances in neural Information processing systems, 2014(27): 2204-2212. |
|
||
