- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Abstract and Applied Analysis
Volume 2012 (2012), Article ID 579543, 9 pages
Structural Learning about Directed Acyclic Graphs from Multiple Databases
School of Mathematical Sciences, Shandong Normal University, Jinan 250014, China
Received 5 October 2012; Accepted 19 November 2012
Academic Editor: Xiaodi Li
Copyright © 2012 Qiang Zhao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- R. G. Cowell, A. P. Dawid, S. L. Lauritzen, and D. J. Spiegelhalter, Probabilistic Networks and Expert Systems, Springer-Verlag, New York, NY, USA, 1999.
- S. L. Lauritzen, Graphical Models, Oxford University Press, Oxford, UK, 1996.
- J. Pearl, Causality: Models, Reasoning, and Inference, Cambridge University Press, Cambridge, UK, 2000.
- P. Spirtes, C. Glymour, and R. Scheines, Causation, Prediction and Search, MIT Press, Cambridge, Mass, USA, 2nd edition, 2000.
- X. Xie, Z. Geng, and Q. Zhao, “Decomposition of structural learning about directed acyclic graphs,” Artificial Intelligence, vol. 170, no. 4-5, pp. 422–439, 2006.
- T. Richardson and P. Spirtes, “Ancestral graph Markov models,” The Annals of Statistics, vol. 30, no. 4, pp. 962–1030, 2002.
- A. P. Dawid, “Conditional independence in statistical theory,” Journal of the Royal Statistical Society B, vol. 41, no. 1, pp. 1–31, 1979.
- C. Beeri, R. Fagin, D. Maier, and M. Yannakakis, “On the desirability of acyclic database schemes,” Journal of the Association for Computing Machinery, vol. 30, no. 3, pp. 479–513, 1983.
- C. Berge, Graphs and Hypergraphs, North-Holland Publishing, Amsterdam, The Netherlands, 2nd edition, 1976.
- Z. Geng, K. Wan, and F. Tao, “Mixed graphical models with missing data and the partial imputation EM algorithm,” Scandinavian Journal of Statistics, vol. 27, no. 3, pp. 433–444, 2000.
- I. Beinlich, H. Suermondt, R. Chavez, and G. Cooper, “The ALARM moni- toring system: a case study with two probabilistic inference techniques for belief networks,” in Proceedings of the 2nd European Conference on Artificial Intelligence in Medicine, pp. 247–256, Springer-Verlag, Berlin, Germany, 1989.
- D. Heckerman, “A tutorial on learning with Bayesian networks,” in Learning in Graphical Models, M. I. Jordan, Ed., pp. 301–354, Kluwer Academic, Dodrecht, The Netherlands, 1998.