Visualizing User Communities and Usage Trends of Digital Libraries Based on User Tracking Information

  • Seonho Kim
  • Subodh Lele
  • Sreeram Ramalingam
  • Edward A. Fox
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4312)


We describe VUDM, our Visual User-model Data Mining tool, and its application to data logged regarding interactions of 1,200 users of the Networked Digital Library of Theses and Dissertations (NDLTD). The goals of VUDM are to visualize social networks, patrons’ distributions, and usage trends of NDLTD. The distinctive approach of this research is that we focus on analysis and visualization of users’ implicit rating data, which was generated based on user tracking information, such as sending queries and browsing result sets – rather than focusing on explicit data obtained from a user survey, such as major, specialties, years of experience, and demographics. The VUDM interface uses spirals to portray virtual interest groups, positioned based on inter-group relationships. VUDM facilitates identifying trends related to changes in interest, as well as concept drift. A formative evaluation found that VUDM is perceived to be effective for five types of tasks. Future work will aim to improve the understandability and utility of VUDM.


Digital Library Collaborative Filter Concept Drift Information Visualization Explicit Data 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Seonho Kim
    • 1
  • Subodh Lele
    • 1
  • Sreeram Ramalingam
    • 1
  • Edward A. Fox
    • 1
  1. 1.Department of Computer ScienceVirginia TechBlacksburgUSA

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