New Advances in Logic-Based Probabilistic Modeling by PRISM

  • Taisuke Sato
  • Yoshitaka Kameya
Conference paper

DOI: 10.1007/978-3-540-78652-8_5

Volume 4911 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Sato T., Kameya Y. (2008) New Advances in Logic-Based Probabilistic Modeling by PRISM. In: De Raedt L., Frasconi P., Kersting K., Muggleton S. (eds) Probabilistic Inductive Logic Programming. Lecture Notes in Computer Science, vol 4911. Springer, Berlin, Heidelberg

Abstract

We review a logic-based modeling language PRISM and report recent developments including belief propagation by the generalized inside-outside algorithm and generative modeling with constraints. The former implies PRISM subsumes belief propagation at the algorithmic level. We also compare the performance of PRISM with state-of-the-art systems in statistical natural language processing and probabilistic inference in Bayesian networks respectively, and show that PRISM is reasonably competitive.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Taisuke Sato
    • 1
  • Yoshitaka Kameya
    • 1
  1. 1.Tokyo Institute of Technology, Ookayama Meguro TokyoJapan