Babes-Bolyai University of Cluj-Napoca
Faculty of Mathematics and Computer Science
Study Cycle: Master
SUBJECT

Code	Subject	
MML1017	Knowledge Discovery and WEB Semantics	

Section	Sem.	Hours: C+S+L	Category	Type	
Intelligent Systems - in English	2	2+1+0	speciality	compulsory	

Teaching Staff in Charge	Lect. SACAREA Cristian, Ph.D., csacarea@math.ubbcluj.ro	
Aims	&#8226;	Making available a broad range of methods for Knowledge Representation and Processing, and Knowledge Engineering.
&#8226;	To discover the underlying formal structure of knowledge, to derive knowledge. 
&#8226;	Knowledge landscape paradigm. 
&#8226;	To develop the student@s ability to understand the problems involved in the formalization of informal data. 
&#8226;	To teach practical skills for representing knowledge by computers. 
&#8226;	To provide practical experience with techniques of structuring graphical representations.
&#8226;	To provide techniques for preprocessing data sets, including the concept of a Data Warehouse
&#8226;	To provide models for automatically learning methods.	
Content	&#8226;	Introduction: Conceptual Knowledge Processing
&#8226;	Conceptual Theory Building
&#8226;	Formal Concept Analysis
&#8226;	Conceptual Graphs
&#8226;	Power Context Families
&#8226;	Ontologies
&#8226;	Knowledge Discovery and Data Mining
&#8226;	Knowledge Discovery in Databases
&#8226;	Decision Trees
&#8226;	Neuronal networks
&#8226;	Association rules
&#8226;	Knowledge Representation
&#8226;	Semantic Web
&#8226;	Applications	
Bibliography	1.	M. Ester und J. Sander: Knowledge Discovery in Databases: Springer-Verlag, 2000. 
2.	U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth and R. Uthurasamy: Advances in Knowledge Discovery and Data Mining. Cambridge , London . MIT Press, 1996.
3.	Frank Vogt, Formal Concept Analysis with C++, Springer, 1996
4.	Rokia Missaoui, Jürg Schmid, eds., Formal Concept Analysis, Springer LNAI 3874, 2006.
5.	B. Ganter, R. Wille, Formal Concept Analysis, Mathematical Foundations, Springer 2000.
6.	G. Antoniou, F. van Harmelen: A Semantic Web Primer. MIT Press, Cambridge 2004.
7.	Online Course in Knowledge Representation using Conceptual Graphs, Aalborg University@s Department of Communication.
8.	J. Sowa: Knowledge Representation, Logical, Philosophical, and Computational Foundations. Brooks/Cole, Pacific Grove 2000.

Assessment	The activity ends with a written final exam (grade E) and a practical project during the semester (grade P). The exam subjects have theoretical questions from all the studied topics, and one problem, among the problems studied at the course and seminar. The final grade arithmetical mean of the two grades mentioned above, conditioned by all the grades being at least 5. Otherwise, the exam will not be passed. The final grade = (E + P)/2.