Advertisement

On Mediated Search of the United States Holocaust Memorial Museum Data

  • Jefferson Heard
  • Jordan Wilberding
  • Gideon Frieder
  • Ophir Frieder
  • David Grossman
  • Larry Kane
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4032)

Abstract

The United States Holocaust Memorial Museum (USHMM) recently celebrated its ten-year anniversary. The museum was established to bear witness to the human atrocities committed by the Nazi reign of terror. As such, related data must be collected, and means to store, search, and analyze the data must be provided. Presently, the data avail- able reside in various formats, sizes, and structures, in videotape and films, in microfilms and microfiche, in various incompatible structured databases, as unstructured electronic documents, and semi-structured indexes scattered throughout the organizations. Collected data are par- titioned over more than a dozen languages, further complicating their processing. There is currently no single search mechanism or even de- partment of human experts that can sift through all the data in a fash- ion that provides global, uniform access. We are currently experimenting with our developed Intranet Mediator technology to provide answers, rather than a potential list of sources as provided by common search en- gines, to questions posed in natural language by Holocaust researchers. A description of a prototype that uses a subset of the data available within the USHMM is described.

Keywords

Priority Queue Execution Plan XPath Query Question Answering System Query Module 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Eyheramendyl, S., Genkin, A., Ju, W., Lewis, D., Madigan, D.: Sparse Bayesian Classifiers for Text Categorization. Journal of Intelligence Community Research and Development 13 (2003)Google Scholar
  2. 2.
    Frieder, O., Grossman, D.: Intranet Mediator. US Patent #6 904, 428 (2005)Google Scholar
  3. 3.
    Grossman, D., Beitzel, S., Jensen, E., Frieder, O.: IIT Intranet Mediator: Bringing data together on a corporate intranet. IEEE IT PRO (January/February 2002)Google Scholar
  4. 4.
    Grossman, D., Frieder, O.: Information Retrieval: Algorithms and Heuristics, 2nd edn. Springer, Heidelberg (2004)MATHGoogle Scholar
  5. 5.
    Infantes-Morris, T., Bernhard, P., Fox, K., Faulkner, G., Stripling, K.: Industrial Evaluation of a Highly-Accurate Academic IR System. ACM CIKM, New Orleans, Louisiana (2003)Google Scholar
  6. 6.
    Jurafsky, D., Martin, J.: Speech and Language Processing, pp. 577–583. Prentice-Hall, Englewood Cliffs (2000)Google Scholar
  7. 7.
    Katz, B., Marton, G., Borchardt, G., Brownell, A., Felshin, S., Loreto, D., Louis-Rosenberg, J., Lu, B., Mora, F., Stiller, S., Uzuner, O., Wilco, A.: External Knowledge Sources for Question Answering. In: The Proceedings of TREC 2005, Gaithersburg, Maryland (November 2005)Google Scholar
  8. 8.
    Manning, C., Schutze, H.: Foundations of Statistical Natural Language Processing, p. 353. MIT Press, Cambridge (1999)MATHGoogle Scholar
  9. 9.
    Nyberg, E., Frederking, R., Mitamura, T., Bilotti, M., Hannan, K., Hiyakumoto, L., Ko, J., Lin, F., Lita, L., Pedro, V., Schlaikjer, A.: JAVELIN I and II Systems at TREC 2005. In: The Proceedings of TREC 2005, Gaithersburg, Maryland (2005)Google Scholar
  10. 10.
    The Python Language, http://www.python.org

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jefferson Heard
    • 1
  • Jordan Wilberding
    • 1
  • Gideon Frieder
    • 1
  • Ophir Frieder
    • 1
  • David Grossman
    • 1
  • Larry Kane
    • 1
  1. 1.Information Retrieval Lab, Illinois Institute of Technology 

Personalised recommendations