|
|
|
| Visualizing Appropriation of Research Funding with t-SNE Algorithm |
Chen Ting1,2,3( ), Li Guopeng3, Wang Xiaomei3 |
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China
2University of Chinese Academy of Sciences, Beijing 100049, China
3Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China |
|
|
|
|
Abstract [Objective] This paper designs a visualization method for the appropriation of research funding, aiming to more effectively present the locations of funded projects. [Methods] First, we retrieved 4,669 funded projects from NSF’s Information and Intelligent System. Then, we added topic tags to these projects using clustering algorithm and human interpretation. Third, we extracted the high-dimensional text features for the application documents with TF-IDF model and LSA model. Fourth, we used the t-SNE algorithm to project high-dimensional features into two or three-dimensional spaces for visualization. Finally, we examined the visualization results with pre-classified topic labels. [Results] The proposed method created maps of funded projects, in both two-dimensional or three-dimensional spaces. [Limitations] The algorithm parameters need to be adjusted manually. More research is needed to evaluate the proposed method with documents of projects funded by other agencies. [Conclusions] The proposed method could generate maps for the funded projects, which is a helpful tool for scientific management.
|
|
Received: 07 March 2018
Published: 08 September 2018
|
|
|
| [1] |
Talley E M, Newman D, Mimno D, et al.Database of NIH Grants Using Machine-Learned Categories and Graphical Clustering[J]. Nature Methods, 2011, 8(6): 443-444.
doi: 10.1038/nmeth.1619
pmid: 21623347
|
| [2] |
陈挺, 韩涛, 李泽霞, 等. 科研项目布局差异对比方法研究——以NSF和EUFP项目为例[J]. 现代图书情报技术, 2015(7-8): 89-96.
|
| [2] |
(Chen Ting, Han Tao, Li Zexia, et al.Research on Comparison Method of Scientific Funding Layout——Take NSF and EUFP Grants for Instance[J]. New Technology of Library & Information Service, 2015(7-8): 89-96.)
|
| [3] |
陈挺, 李国鹏, 姜山, 等. NSF材料科学十年——基金项目分布及趋势变化分析[J]. 世界科技研究与发展, 2017, 39(5): 401-411.
|
| [3] |
(Chen Ting, Li Guopeng, Jiang Shan, et al.Past Decade of NSF Material Science:An Analysis of Layout and Trend of Funded Projects[J]. World Sci-Tech R&D, 2017, 39(5): 401-411.)
|
| [4] |
De-Miguel-Molina B, Cunningham S W, Palop F. Analyzing Funding Patterns and Their Evolution in Two Medical Research Topics[J]. International Journal of Innovation and Technology Management, 2017, 14(2). DOI: 10.1142/S0219877017400107.
doi: 10.1142/S0219877017400107
|
| [5] |
王文娟, 马建霞. 基于LDA的科研项目主题挖掘与演化分析——以NSF海洋酸化研究为例[J]. 情报杂志, 2017, 36(7): 34-39.
doi: 10.3969/j.issn.1002-1965.2017.07.007
|
| [5] |
(Wang Wenjuan, Ma Jianxia.Topic Detection and Evolution Analysis of Research Project Based on LDA——A Case Study of Projects on Ocean Acidification Supported by NSF[J]. Journal of Intelligence, 2017, 36(7): 34-39.)
doi: 10.3969/j.issn.1002-1965.2017.07.007
|
| [6] |
Park J, Blume-Kohout M, Krestel R, et al.Analyzing NIH Funding Patterns over Time with Statistical Text Analysis[C]// Proceedings of the 30th AAAI Conference on Artificial Intelligence. 2016.
|
| [7] |
Liu S, Cao N, Lv H. Interactive Visual Analysis of the NSF Funding Information[C]//Proceedings of 2008 IEEE Pacific Visualization Symposium. DOI: 10.1109/PACIFICVIS.2008.4475475.
|
| [8] |
王贤文, 刘则渊, 侯海燕. 全球主要国家的科学基金及基金论文产出现状: 基于Web of Science的分析[J]. 科学学研究, 2010, 28(1): 62-66.
|
| [8] |
(Wang Xianwen, Liu Zeyuan, Hou Haiyan.Global Assessment of Science Funding and Funding Papers: A Study in Web of Science[J]. Studies in Science of Science, 2010, 28(1): 62-66.)
|
| [9] |
孙金伟, 刘迪, 王贤文, 等. 科学基金资助与SCI论文产出: 对10个国家的比较分析[J]. 科学学研究, 2013, 31(1): 36-42.
doi: 10.3969/j.issn.1003-2053.2013.01.006
|
| [9] |
(Sun Jinwei, Liu Di, Wang Xianwen, et al.Science Funding and SCI Papers Output: A Comparative Analysis on 10 Countries[J]. Studies in Science of Science, 2013, 31(1): 36-42.)
doi: 10.3969/j.issn.1003-2053.2013.01.006
|
| [10] |
Auranen O, Nieminen M.University Research Funding and Publication Performance - An International Comparison[J]. Research Policy, 2010, 39(6): 822-834.
doi: 10.1016/j.respol.2010.03.003
|
| [11] |
Wang J, Shapira P.Funding Acknowledgement Analysis: An Enhanced Tool to Investigate Research Sponsorship Impacts: The Case of Nanotechnology[J]. Scientometrics, 2011, 87(3): 563-586.
doi: 10.1007/s11192-011-0362-5
|
| [12] |
Herr II B W, Talley E M, Burns G A P C, et al. The NIH Visual Browser: An Interactive Visualization of Biomedical Research[C]// Proceedings of the 13th International Conference on Information Visualisation. IEEE, 2009.
|
| [13] |
Takahiro K, Katsutaro W, Naoya M.Funding Map for Research Project Relationships Using Paragraph Vectors[C]// Proceedings of the 16th International Conference on Scientometrics&Informetrics (ISSI), Wuhan, China. 2017.
|
| [14] |
Abadi M, Agarwal A, Barham P, et al. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems[OL]. arXiv:1603.04467. 2016.
|
| [15] |
Salton G, Buckley C.Term-Weighting Approaches in Automatic Text Retrieval[J]. Information Processing & Management,1988, 24(5): 513-523.
doi: 10.1016/0306-4573(88)90021-0
|
| [16] |
Foltz P W.Latent Semantic Analysis for Text-based Research[J]. Behavior Research Methods Instruments & Computers, 1996, 28(2): 197-202.
doi: 10.3758/BF03204765
|
| [17] |
Roweis S T, Saul L K.Nonlinear Dimensionality Reduction by Locally Linear Embedding[J]. Science, 2000, 290(5500): 2323-2326.
doi: 10.1126/science.290.5500.2323
pmid: 11125150
|
| [18] |
Burges C J C. Dimension Reduction: A Guided Tour[J]. Foundations & Trends® in Machine Learning, 2010, 2(4): 262-286.
doi: 10.1561/2200000002
|
| [19] |
Zhong G, Cheriet M.Large Margin Low Rank Tensor Analysis[J]. Neural Computation, 2014, 26(4):761-780.
doi: 10.1162/NECO_a_00570
pmid: 24479778
|
| [20] |
Li W, Cerise J E, Yang Y, et al.Application of t-SNE to Human Genetic Data[J]. Journal of Bioinformatics & Computational Biology, 2017, 15(4): 1750017. DOI: 10.1142/S0219720017500172.
doi: 10.1142/S0219720017500172
pmid: 28718343
|
| [21] |
Pezzotti N, Lelieveldt B, Maaten L V D, et al. Approximated and User Steerable tSNE for Progressive Visual Analytics[J]. IEEE Transactions on Visualization & Computer Graphics, 2017, 23(7): 1739-1752.
doi: 10.1109/TVCG.2016.2570755
pmid: 27323366
|
| [22] |
Liu S, Bremer P T, Thiagarajan J J, et al.Visual Exploration of Semantic Relationships in Neural Word Embeddings[J]. IEEE Transactions on Visualization & Computer Graphics, 2017, 24(1): 553-562.
doi: 10.1109/TVCG.2017.2745141
pmid: 28866574
|
| [23] |
Maaten L V D, Hinton G. Visualizing Data Using t-SNE[J]. Journal of Machine Learning Research, 2008, 9(2605): 2579-2605.
doi: 10.1007/s10846-008-9235-4
|
| [24] |
Hinton G, Roweis S.Stochastic Neighbor Embedding[J]. Advances in Neural Information Processing Systems, 2002, 41(4): 833-840.
|
| [25] |
Kullback S, Leibler R A.On Information and Sufficiency[J]. Annals of Mathematical Statistics, 1951, 22(1): 79-86.
doi: 10.1214/aoms/1177729694
|
| [26] |
Embedding Projector[EB/OL]. [2018-02-20]. .
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
