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Multi-level Exploration of Citation Graphs

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3232))

Abstract

In previous work, we proposed a focus-based multi-level clustering technique. It consists in computing a particular clustered graph from a given graph and a focus. The resulting clustered graph is called multi-level outline tree. It is a tree whose meta-nodes are sub-sets of nodes. A meta-node is itself hierarchically clustered depending on its connectivity. In this paper we introduce a cluster cohesiveness measure to enhance the results of the previously proposed algorithm. We further propose an optimization of this algorithm to support fluid interaction when focus changes. Finally, we report the results of a case study that consists in applying the enhanced algorithm to citation graphs where documents are considered as vertices and citation links as edges.

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References

  1. An, Y., Janssen, J.C.M., Milios, E.E.: Characterizing the Citation Graph as a Self-Organizing Networked Information Space. IICS, 97–107 (2002)

    Google Scholar 

  2. Boutin, F., Hascoët, M.: Cluster Validity Indices for Graph Partitioning. In: Proceedings of the Conference on Information Visualization IV (2004)

    Google Scholar 

  3. Boutin, F., Hascoët, M.: Focus Dependent Multi-level Graph Clustering. In: Proceedings of the Conference on Advanced Visual Interfaces, AVI, ACM, New York (2004)

    Google Scholar 

  4. Boutin, F., Hascoët, M.: Focus-Based Clustering for Multi-Scale Visualization. In: Proceedings of the Conference on Information Visualization, IV 2003, pp. 53–59. IEEE, Los Alamitos (2003)

    Chapter  Google Scholar 

  5. Brandes, U., Willhalm, T.: Visualization of bibliographic networks with a reshaped landscape metaphor. In: Proceedings of the symposium on Data Visualisation 2002, p. 159 (2002)

    Google Scholar 

  6. Brockenauer, R., Cornelsen, S.: Drawing Clusters and Hierarchies. In: Kaufmann, M., Wagner, D. (eds.) Drawing Graphs. LNCS, vol. 2025, pp. 194–228. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  7. Chen, C.: Visualizing Semantic Spaces and Author Co-Citation Networks in Digital Libraries. Information Processing & Management 35, 401–420 (1999)

    Article  Google Scholar 

  8. Eades, P.: Multilevel Visualization of Clustered Graphs. In: Proceedings of Graph Drawing 1996, Berkeley, California (September1996)

    Google Scholar 

  9. Han, E.-H., Karypis, G.: Centroid-Based Document Classification: Analysis and Experimental Results. In: Proc. of the 4th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) (September 2000)

    Google Scholar 

  10. Hascoët, M.: Interaction and visualisation supporting web browsing patterns. In: Information Visualization, IV 2001, London, pp. 413–419. IEEE, Los Alamitos (2001)

    Google Scholar 

  11. Kohonen, T.: Self-Organizing Maps. Springer, New York (1997)

    MATH  Google Scholar 

  12. Lawrence S., Bollacker K., Giles C. L.: ResearchIndex. NEC Research Institute, IST Information Sciences and Technology, http://citeseer.ist.psu.edu/

  13. Plaisant, C., Grosjean, J., Bederson, B.B.: SpaceTree: Supporting Exploration in Large Node Link Tree. In: Design Evolution and Empirical Evaluation INFOVIS 2002, Boston, October 2002, pp. 57–64. IEEE, Los Alamitos (2002)

    Google Scholar 

  14. Roxborough, T., Sen, A.: Graph clustering using multiway ratio cut. In: DiBattista, G. (ed.) GD 1997. LNCS, vol. 1353, pp. 291–296. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  15. Steinbach, M., Karypis, G., Kumar, V.: A Comparison of Document Clustering Techniques. In: Proc. TextMining Workshop, KDD (2000)

    Google Scholar 

  16. Weiss, R., Velez, B., Sheldon, M.A., Nemprempre, C., Szilagyi, P., Duda, A.: Hypursuit: A hierarchical network search engine that exploits content-link hypertext clustering. In: Proc. of the 7th ACM Conf. on Hypertext (1996)

    Google Scholar 

  17. Wang, Y., Kitsuregawa, M.: Link based clustering of web search results. In: Wang, X.S., Yu, G., Lu, H. (eds.) WAIM 2001. LNCS, vol. 2118, pp. 225–236. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Boutin, F., Hascoët, M. (2004). Multi-level Exploration of Citation Graphs. In: Heery, R., Lyon, L. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2004. Lecture Notes in Computer Science, vol 3232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30230-8_33

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  • DOI: https://doi.org/10.1007/978-3-540-30230-8_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23013-7

  • Online ISBN: 978-3-540-30230-8

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