[ 1 ] 中国家谱知识服务平台[EB/OL]. [2019-09-02].
http://jiapu.library.sh.cn/#/.
[ 2 ] 全国报刊索引[EB/OL]. [2019-09-02]. http://www.
cnbksy.com/.
[ 3 ] 毛建军. 古籍数字化概念的形成过程探析[J]. 科
技情报开发与经济, 2006, 16 (22): 160-162.
[ 4 ] 黄水清, 毛东波. 古文信息处理研究的现状及趋
势[J]. 图书情报工作, 2017, 61 (12): 43-49.
[ 5 ] 张鹏立. 浅谈中国古代书信[J]. 河北省社会主义
学院学报, 2014 (2) .
[ 6 ] 吕瑞花, 韩晶晶, 韩露. 基于元数据的科技名人档
案编目[J]. 科技导报, 2013, 31 (14): 64-69.
[ 7 ] 李惠, 侯君明. 古代书信体文献的社交网络模型[J].
南京师范大学文学院学报, 2018(3): 164-172.
[ 8 ] Darwin Correspondence Project[EB/OL]. [2019-09-
02]. http://www.darwinproject.ac.uk/.
[ 9 ] Thomas Bodley [EB/OL]. [2019-09-02]. http://
www.livesandletters.ac.uk/projects/diplomaticcorrespondence-thomas-bodley-1585-1597.
[10] The Newton Project[EB/OL]. [2019-09-02]. http://
www.newtonproject.ox.ac.uk.
[11] Lightman B. Correspondence Networks [M]. A
Companion to the History of Science. John Wiley &
Sons, Hoboken. 2016.
[12] Circulation of Knowledge and Learned Practices in
the 17th-century Dutch Republic[EB/OL]. [2019-
09-02]. http://ckcc.huygens.knaw.nl/.
[13] Early Modern Letters Online[EB/OL]. [2019-09-02].
http://www.livesandletters.ac.uk.
[14] Mapping the Republic of Letters.[2019-09-02].
http://republicofletters.stanford.edu/.
[15] Blei D M, Ng A Y, Jordan M I. Latent Dirchlet
Allocation[J]. Journal of Machine Learning Research,
2003, 3 (1): 993-1022.
[16] Blei D M. Probabilistic Topic Models[J].
Communications of the ACM, 2012, 55 (4): 77-84.
[17] Comprehending the Digital Humanities[EB/
OL]. [2019-09-02]. https: //dhs.stanford.edu/
comprehending-the-digital-humanities/.
[18] Nelson R K. Mining the Dispatch[EB/OL]. [2019-
09-02]. https: //dsl.richmond.edu/dispatch/.
[19] Mimno D. Computational Historiography: Data
Mining in a Century of Classics Journals[J]. Journal
on Computing and Cultural Heritage, 2012, 5 (1):
1-19.
[20] Keli Du. A Survey on LDA Topic Modeling in Digital
Humanities[EB/OL]. [2019-09-02]. https://dev.
clariah.nl/files/dh2019/boa/0326.html.
[21] Li H.Social Network Extraction and Exploration
of Historic Correspondences [D]. Heidelberg:
Heidelberg University, 2018.
[22] Kullback S, Leibler R A. On Information and
Sufficiency[J]. Annals of Mathematical Statistics,
1951(22): 79-86.
[23] Lin J. Divergence Measures based on the Shannon
Entropy[J]. IEEE Transactions on Information
Theory, 1991, 33 (1): 145-151.
[24] 曾国藩. 曾国藩全集[M]. 长沙: 岳麓书社, 2011.
[25] 唐浩明. 唐浩明评点曾国藩书信[M]. 长沙: 岳麓
书社, 2011: 1-6.
[26] 李筱瑜. 基于新词发现与词典信息的古籍文本分
词研究[J]. 软件导刊, 2019, 18 (4): 60-63.
[27] Lin Y, Michel J B, Aiden E L, et al. Syntactic
Annotations for the Google Books Ngram Corpus[C].
Proceedings of the Association for Computational
Linguistics (System Demonstrations), 2012: 169-
174.
[28] Chinese Text Segmentation with R[EB/OL]. [2019-
09-02]. https: //github.com/qinwf/jiebaR.
[29] Ramos J. Using TF-IDF to Determine Word
Relevance in Document Queries[C]. Proceedings
of the First Instructional Conference on Machine
Learning, 2003, 242: 133-142.
[30] Griffiths T L, Steyvers M. Finding Scientific
Topics[J]. Proceedings of the National Academy of
Sciences 101 (Suppl_1) 2004: 5228-5235.
[31] Juan C, Tian X, Tao L J, et al. Density-based Method
for Adaptive LDA Model Selection[J]. Journal
Neurocomputing. 2009, 72 (7-9): 1775-1781.
[32] R?der M, Both A, Hinneburg A. Exploring the Space
of Topic Coherence Measures[C]. Proceedings of
the Eighth ACM International Conference on Web
Search and Data Mining. 2015: 399-408.
[33] 陈松溪. 关于郑振铎的家世[J]. 固原师专学报 (社
会科学), 1997 (2): 1-6.
[34] 龙方成. 试论曾国藩的后勤保障思想[J]. 湖湘论
坛, 1994 (6): 54-57.
[35] 孙经超. 清代衍圣公行政职权研究[D]. 曲阜: 曲
阜师范大学, 2018.
[36] 王丽娇. 晚清疆臣吴文镕[D]. 长春: 东北师范大
学, 2014.
[37] 仝群旺. 青果巷与“中国商父”盛宣怀[J]. 档案
与建设, 2017: 40-41.
[38] 董明月. 洋务运动对中国近代化的影响[D]. 长春:
吉林大学, 2009.
[39] Blondel V D, Guillaume J L, Lambiotte R, et al. Fast
Unfolding of Communities in Large Networks[J].
Journal of Statistical Mechanics: Theory and
Experiment, 2008 (10): 10008.
[40] Albert-László Barabási and Márton Pósfai.
Network Science[M]. Cambridge: Cambridge
University Press, 2016: 355-375.
[41] 吴煊; 吴安谷.读史笔记[EB/OL]. [2019-12-20].
https://chinese-cat.lib.cam.ac.uk/mulu/fb85.html.
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