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Weimao Ke

Weimao Ke

Associate Professor

Information Science

Dr. Ke's research is centered on information retrieval (IR), particularly the investigation of intelligent systems that support better connection and interaction between people and information. His recent focus is on decentralized IR functions that can adapt and scale in continuously growing and increasingly interconnected information spaces. His broad interests also include complex networks/systems, text mining, information visualization, bibliometrics, machine learning, multi-agent systems, and the notion of information. Dr. Ke's major teaching interests include IR, databases, data mining, software/web development, and complex systems.


  • PhD, Information Science, University of North Carolina at Chapel Hill
  • MA, Information Science, Indiana University Bloomington
  • BE, Chemical Engineering, East China University of Science & Technology

Research/Teaching Interests

Information retrieval (IR), distributed systems, intelligent filtering/recommendation, information visualization, network science, complex systems, machine learning, text/data mining, multi-agent systems

Select Publications

  • Weimao Ke (2013). Information-theoretic Term Weighting Schemes for Document Clustering. In JCDL’13: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, pp. 143-152. Indianapolis, IN.
  • Weimao Ke and Javed Mostafa (2013). Studying the Clustering Paradox and Scalability of Search in Highly Distributed Environments. ACM Transactions on Information Systems, 31(2), pp. 8:1-8:36. ACM Press.
  • Weimao Ke (2013). A Fitness Model for Scholarly Impact Analysis. Scientometrics, 94(3), pp. 981-998. OnlineFirst July 2012. Springer.
  • Weimao Ke and Javed Mostafa (2010). Scalability of Findability: Efficient and Effective IR Operations in Large Information Networks. In SIGIR ’10: Proceedings of the 33nd annual international ACM SIGIR conference on research and development in information retrieval, pp. 74-81. Geneva, Switzerland. July 19-23, 2010.
  • Weimao Ke, Cassidy R. Sugimoto, and Javed Mostafa (2009). Dynamicity vs. effectiveness: Studying online clustering for Scatter/Gather. In SIGIR ’09: Proceedings of the 32nd annual international ACM SIGIR conference on research and development in information retrieval, pp. 19-26. Boston, MA. July 19-23, 2009.

Awards & Recognition

  • Recipient of the Outstanding Online Faculty Award, Drexel University, Philadelphia PA, 2013
  • Nominee for the Vannevar Bush Best Paper Award, ACM&IEEE JCDL, Indianapolis IN, 2013
  • Best Paper award nominee, International Conf on Weblog & Social Media, AAAI, Boulder CO, 2007
  • First Place Award (of 18 teams internationally), InfoVis 2004 Contest, IEEE, Austin TX, 2004 

Professional Activities & Associations

  • Association for Computing Machinery (ACM)
  • ACM Special Interest Group on Information Retrieval (ACM SIGIR)
  • American Society for Information Science and Technology (ASIS&T)