Understanding outside collaborations of the Chinese Academy of Sciences using Jensen-Shannon divergence

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7243, Issue , 2009, Pages

  Duhon, Russell ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHINESE ACADEMY OF SCIENCES; COLLABORATION PATTERNS; JENSEN-SHANNON DIVERGENCES; SCIENCE POLICIES;

VISUALIZATION;

DATA VISUALIZATION;

EID: 62349117259     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.812383     Document Type: Conference Paper

References (30)

1. Ahlgren, Per, Bo Jarneving, Ronald Rousseau. (2003). Requirements For a Cocitation Similarity Measure, with Special Reference to Pearson's Correlation Coefficient. Journal of the American Society for Information Science and Technology, 54 (6), 550-560.
2. Anderberg, M. R. (1973). Cluster Analysis for Applications. New York: Academic Press, Inc.
3. Bayer, A. E., J. C. Smart, G. W. McLaughlin. (1990). Mapping Intellectural Structure of a Scientific Subfield Through Author Cocitations. Journal of the American Society for Information Science, 41 (6), 444-452.
4. Bensman, Stephen J. (2004). Letter to the Editor: Peearson's r and Author Cocitation Analysis: A Commentary on the Controversy. Journal of the American Society for Information Science and Technology, 55 (10), 935-936.
5. Boyack, Kevin W., Katy Borner, Richard Klavans. (2007). Mapping the Structure and Evolution of Chemistry Research. Paper presented at the 11th International Conference of the International Society for Scientometrics and Informetrics, Madrid Spain: Consejo Superior de Investigciones Cientificas, pp. 112-123.
6. Boyack, Kevin W., Richard Klavans, Katy Böner. (2005). Mapping the Backbone of Science. Scientometrics, 64 (3), 351-374.
7. Butte, A. J., I. S. Kohane. (2000). Mutual Information Relevance Networks: Functional Genomic Clustering Using Pairwise Entropy Measurements. Pacific Symposium on Biocomputing, 5, 415-426.
8. Chen, Chaomei. (1994). Information Visualization: Beyond the Horizon. New York: Springer.
9. Endres, D. M., J. E. Schindelin. (2003). A New Metric for Probability Distribution. IEEE Transactions on Information Theory, 49 (7), 1858-1860.
10. Everitt, B. S. (1974). Cluster Analysis. London: Heinemann.
11. Gibbons, F. D., F. P. Roth. (2002). Judging the Quality of Gene Expression-Based Clustering Methods Using Gene Annotation. Genome Research 12, 1574-1581.
12. Grosse, Ivo, Pedro Bernaola-Galván, Pedro Carpena, Ramón Román-Roldán, Jose Oliver, H. Eugene Stanley. (2002). Analysis of Symbolic Sequences Using the Jensen-Shanoon Divergence. Physical Review E., 65 (014905).
13. Klavans, Richard, Kevin W. Boyack. (2006). Identifying a Better measure of Relatedness for Mapping Science. Journal of the American Society for Information Science and Technology, 57 (2), 251-263.
14. Leydesdorff, Loet. (2005). Similarity Measures, Author Cocitation Analysis and Information Theory. Journal of the American Society for Information Science and Technology, 56 (7), 769-772.
15. Leydesdorff, Loet. (2008). On the Normalization and Visualization of Author Co-Citation Data: Saton's Cosine Versus the Jaccard Index. Journal of the American Society for Information Science and Technology, 59 (1), 77-85.
16. Leydesdorff, Loet, Liwen Vaughan. (2006). Co-occurrence matrices and Their Applications in Information Science: Extending ACA to the Web Environment. Journal of the American Society for Information Science and Technology, 57 (12), 1616-1628.
17. Lin, J. (1991). Divergence Measures Based on the Shannon Entropy. IEEE Transactions on Information Theory, 37 (1), 145-151.
18. Marshakova, I. V. (1973). Co-Citation in Scientific Literature: A New Measure of the Relationship Between Publications. Scientific and Technical Information Serial of VINITI 6, 3-8.
19. Newman, M. E.J. (2004). Who is the Best Connected Scientist? A Study of Scientific Coauthorship Networks. In E. Ben-Haim, H. Frauenfelder & Z. Toroczkai (Eds.), Complex Networks, lecture Notes in Physics (Vol. 650, pp. 337-370).
20. Osterreicher, Ferdinand, Igor Vajda. (2003). A New Class of Metric Divergences on Probability Spaces and its Applicability in Statistics. Annals of the Institute of Statistical Mathematics, 55 (3), 639-653.
21. Schvaneveldt, R (Ed.). (1990). Pathfinder Associative Networks: Studies in Knowledge Organization. Norwood, NJ: Ablex Publishing.
22. Small, Henry. (1973). Co-Citation in Scientific Literature: A New Measure of the Relationship Between Publications. Journal of the American Society for Information Science 24, 265-269.
23. Small, Henry. (2006). Tracking and Predicting Growth Areas in Science. Scientometrics, 63 (3), 595-610.
24. Small, Henry, Belver C. Griffith. (1974). The Structure of Scientific Literatures I: Identifying and Graphing Specialites. 4, 7 (17-40).
25. Small, Henry, E. Sweeney. (1985). Clustering the Science Citation Index® Using Co-Citations: I. A Comparison of Methods. Scientometrics, 7 (3-6), 391-409.
26. Topsoe, F. (2000). Some Inequalities for Information Divergence and Related Measures of Discrimination. IEEE Transactions on Information Theory, 46 (4), 1602-1609.
27. Wallace, M. L., Yves Gingras, Russell Duhon. (2009). A New Approach for Detecting Scientific Specialites from Raw Cocitation Networks. Journal of the American Society for Information Science and Technology,.
28. White, Howard D. (2003). Author Cocitation Analysis and Pearson's r. Journal of the American Society for Information Science and Technology, 54 (13), 1250-1259.
29. White, Howard D., Belver C. Griffith. (1981). Author Cocitation: A Literature Measure of Intellectual Structure. Journal of the American Society for Information Science 32 (163-172).
30. Wong, A., M. You. (1985). Entropy and Distance of Random Graphs with Application to Structural Pattern Recognition. Pattern Analysis and Machine Intelligence, 7, 599-609.