











The aim of this project is to provide a framework for experimentation and solving practical problems in the area of relational learning and first order inference. By using this framework students can:
 Learn the basics of Relational Learning and its application to web document classification.
 Gain experience in using software applications in these areas for solving practical problems.
 Better understand the fundamentals of FirstOrder Logic, Learning and Reasoning in FirstOrder Logic, which are basic components of the wider area of knowledge representation and reasoning in AI.













Students should have basic knowledge of discrete mathematics and logic. Some programming experience in Prolog would be helpful as most of the software tools used in the project are implemented in Prolog and Prolog is also the representation language for FirstOrder Learning.
The software packages and data sets used in the project are freely available on the Web:













It is recommended that before starting the project students read Chapters 8, 9, and 19 of Russell and Norvig’s book ([1]), Chapter 1 and Chapter 5 (Section “Relational Learning”) of Markov and Larose’s book ([2]), or Chapter 10 of Mitchell’s book ([3]). While installing and experimenting with Prolog they may use a Prolog tutorial ([4,5]).
 Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach, 2nd edition. Prentice Hall, Upper Saddle River, NJ, USA, 2003.
 Zdravko Markov and Daniel T. Larose. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage. Wiley, 2007. Chapter 1 is available for download from Wiley.
 Tom Mitchell. Machine Learning. McGraw Hill, 1997.
 Ian H. Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques, 2nd edition. Morgan Kaufmann, 2005.
 Quick Introduction to Prolog, available at http://www.cs.ccsu.edu/~markov/ccsu_courses/prolog.txt.
 A Prolog Tutorial by J.R. Fisher, available at http://www.csupomona.edu/~jrfisher/www/prolog_tutorial/contents.html.













The detailed project description is available in the PDF file RelationalLearning.pdf. You will need the free Adobe Acrobat Reader to view this file.


This project is customizable to accommodate different approaches to teaching and different implementations. Additional exercises are also included for students seeking more extended challenges.














A sample syllabus is not available.
Additional readings are included in the Background section above.










