In Chapter 3, we introduced basic principles of cartography for mapping abstract structures commonly resulting from our thinking, ranging from concept mapping based on card sorting, through co-word maps derived from word co-occurrence analysis, to generic structures represented as networks, especially the interesting properties of a class of gigantic graphs known as small-world networks. We described typical dimensionality reduction techniques such as the classic multidimensional scaling (MDS) and the latest advances in non-linear MDS.


Minimum Span Tree Travel Salesman Problem Sandia National Laboratory Information Visualization Latent Semantic Indexing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Boyack, KW, Wylie, BN, Davidson, GS, and Johnson, DK (2000). Analysis of Patent Databases Using Vxinsight (SAND2000–2266C). Albuquerque, NM: Sandia National Laboratories.Google Scholar
  2. Bush, V (1945). As we may think. Atlantic Monthly, 176(1), 101–8.Google Scholar
  3. Chen, C (1998). Generalised similarity analysis and pathfinder network scaling. Interacting with Computers, 10(2), 107–28.CrossRefGoogle Scholar
  4. Chen, C (1999a). Information Visualisation and Virtual Environments. London: Springer.Google Scholar
  5. Chen, C (1999b). Visualising semantic spaces and author co-citation networks in digital libraries. Information Processing and Management, 35(2), 401–20.CrossRefGoogle Scholar
  6. Chen, C, and Carr, L (1999a). Trailblazing the literature of hypertext: author co-citation analysis (1989–1998). Proceedings of the 10th ACM Conference on Hypertext (Hypertext ’99), February 1999, Darmstadt, Germany, pp. 51–60.Google Scholar
  7. Chen, C, and Carr, L (1999b). Visualizing the evolution of a subject domain: a case study. Proceedings of IEEE InfoVis ’99, 24–29 October 1999, San Francisco, CA, USA.Google Scholar
  8. Chen, C, and Czerwinski, M (1998). From latent semantics to spatial hypertext: an integrated approach. Proceedings of the 9th ACM Conference on Hypertext and Hypermedia (Hypertext ’98), June 1998, Pittsburgh, PA, USA, pp. 77–86.Google Scholar
  9. Chen, C, and Paul, RJ (2001). Visualizing a knowledge domain’s intellectual structure. Computer, 34(3), 65–71.CrossRefGoogle Scholar
  10. Chen, C, Gagaudakis, G, and Rosin, P (2000). Content-based image visualisation. Proceedings of IEEE International Conference on Information Visualisation (IV 2000), 19–21 July 2000, London, UK, pp. 13–18.Google Scholar
  11. Chen, H, Houston, AL, Sewell, RR, and Schatz, BR (1998). Internet browsing and searching: user evaluations of category map and concept space techniques. Journal of the American Society for Information Science, 49(7), 582–608.Google Scholar
  12. Crossley, M, Davies, J, McGrath, A, and Rejman-Greene, M (1999). The knowledge garden. BT Technology Journal, 17(1). Scholar
  13. Darken, RP, and Sibert, JL (1996). Wayfinding strategies and behaviors in large virtual worlds. Proceedings of CHI ’96, April 14–18, 1996, Vancouver, BC, pp. 142–9.Google Scholar
  14. Deerwester, S, Dumais, ST, Landauer, TK, Furnas, GW, and Harshman, RA (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391–407.CrossRefGoogle Scholar
  15. Dumais, ST (1995). Using LSI for information filtering: TREC-3 experiments. In: DK Harman (ed.),Proceedings of the Third Text REtrieval Conference (TREC-3), April 1995. NIST Special Publication 500–225, pp. 219–30.Google Scholar
  16. Flickner, M, Sawhney, H, Niblack, W, Sahley, J, Huang, Q, Dom, B, Gorkani, M, Hafner, J, Lee, D,Petkovic, D, Steele, D, and Yanker, P (1995). Query by image and video content: the QBIC system.IEEE Computer, 28(9), 23–32.Google Scholar
  17. Groetschel, M (1977). Polyedrische Charakterisierungen kombinatorischer Optimierungsprobleme.Mathematical Systems in Economics, 36. Meisenheim am Glan: Verlag Anton Hain.Google Scholar
  18. He, DC, and Wang, L (1990). Texture unit, texture spectrum, and texture analysis. IEEE Transactions on Geoscience and Remote Sensing, 28(4), 509–12.MathSciNetCrossRefGoogle Scholar
  19. Hetzler, B, Whitney, P, Martucci, L, and Thomas, J (1998). Multi-faceted insight through interoperable visual information analysis paradigms. Proceedings of IEEE Information Visualization ’98, Oct 19–20, 1998, Los Alamitos, CA, pp. 137–44.Google Scholar
  20. Irwin, NH, van Berkel, J, Johnson, DK, and Wylie, BN (1997). Navigating nuclear science: enhancing analysis through visualization. Sandia Report SAND97–2218, September 1997.CrossRefGoogle Scholar
  21. Kamada, T, and Kawai, S (1989). An algorithm for drawing general undirected graphs. Information Processing Letters, 31, 7–15.MathSciNetzbMATHCrossRefGoogle Scholar
  22. Kohonen, T (1989). Self-organization and Associate Memory (3rd ed.). New York: Springer.Google Scholar
  23. Kruskal, JB (1977). The relationship between multidimensional scaling and clustering. In: J van Ryzin (ed.), Classification and Clustering. New York: Academic Press, pp. 17–44.Google Scholar
  24. Lin, X (1997). Map displays for information retrieval. Journal of the American Society for Information Science, 48(1), 40–54.CrossRefGoogle Scholar
  25. Pirolli, P, and Card, SK (1995). Information foraging in information access environments. Proceedings of CHI ’95, May 7–11, 1995, Denver, CO, USA, pp. 51–8.Google Scholar
  26. Pirolli, P, Pitkow, J, and Rao, R (1996). Silk from a sow’s ear: extracting usable structures from the web.Proceedings of CHI ’96, April 14–18, 1996, Vancouver, BC, pp. 118–25.Google Scholar
  27. Sandstrom, PE (1999). Scholars as subsistence foragers. Bulletin of the American Society for Information Science, 25(3). Scholar
  28. Schrijver, A (2001). On the history of combinatorial optimization (till 1960). (retrieved 6 November 2001).Google Scholar
  29. Schvaneveldt, RW (ed.) (1990). Pathfinder Associative Networks: Studies in Knowledge Organization.Norwood, NJ: Ablex.Google Scholar
  30. Schvaneveldt, RW, Durso, FT, and Dearholt, DW (1989). Network structures in proximity data.In: G Bower (ed.), The Psychology of Learning and Motivation, Vol. 24. New York: Academic Press,pp. 249–84.Google Scholar
  31. Shneiderman, B (1992). Tree visualization with tree-maps: A 2-dimensional space filling approach,ACM Transactions on Graphics 11(1), 92–99.zbMATHCrossRefGoogle Scholar
  32. Shneiderman, B (1996). The eyes have it: a task by data type taxonomy for information visualization.Proceedings of IEEE Workshop on Visual Language, Sept 3–6, 1996, Boulder, CO, pp. 336–43.Google Scholar
  33. Shneiderman, B (1998). Codex, memex, genex: the pursuit of transformational technologies.International Journal of Human-Computer Interaction, 10(2), 87–106.CrossRefGoogle Scholar
  34. Small, H (1986). The synthesis of specialty narratives from co-citation clusters. Journal of the American Society for Information Science, 37(3), 97–110.Google Scholar
  35. Small, H (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799–813.CrossRefGoogle Scholar
  36. Small, H (2000). Charting pathways through science: exploring Garfield’s vision of a unified index to science. Web of Knowledge - A Festschrift in Honor of Eugene Garfield, pp. 449–73.Google Scholar
  37. Swain, M, and Ballard, H (1991). Color indexing. International Journal of Computer Vision, 7, 11–32.CrossRefGoogle Scholar
  38. White, HD, and McCain, KW (1998). Visualizing a discipline: an author co-citation analysis of information science, 1972–1995. Journal of the American Society for Information Science, 49(4),327–56.Google Scholar
  39. Wise, JA (1999). The ecological approach to text visualization. Journal of the American Society for Information Science, 50(13), 1224–33.CrossRefGoogle Scholar
  40. Wise, JA, Thomas, JJ, Pennock, K, Lantrip, D, Pottier, M, Schur, A, and Crow, V (1995). Visualizing the non-visual: spatial analysis and interaction with information from text documents.Proceedings of IEEE Symposium on Information Visualization ’95, 30–31 October 1995, Atlanta,GA, USA, pp. 51–8.Google Scholar

Copyright information

© Springer-Verlag London Limited 2003

Authors and Affiliations

  • Chaomei Chen
    • 1
  1. 1.College of Information Science and TechnologyDrexel UniversityPhiladelphiaUSA

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