Course Catalog 2009-2010 International Basic Pori International Postgraduate Open University |Degrees|     |Study blocks|     |Courses|

Person responsible

Esko Turunen

Implementations

	Lecture times and places	Target group recommended to
Implementation 1	Periods 1 1 - 2

Requirements

Examination or partial examinations.
Completion parts must belong to the same implementation

Principles and baselines related to teaching and learning

-

Learning outcomes

Introduction to data mining, in particular to the GUHA-method and its applications. Application of these methods to real world problems. Introduction to mathematical foundations and applications of various non-classical logics.

Content

Content	Core content	Complementary knowledge	Specialist knowledge
1.	Introduction to data mining; does my data contain something interesting I did not know? The GUHA method: data matrices as finite models, 'almost all', 'in most cases', 'above average' and other non-standard quantifiers.	Introduction to LISpMiner, a software implementation of the GUHA method. Practical data mining tasks by LISp Miner.
2.	Introduction to mathematical fuzzy logic; real life situations where neither black-or-white logic nor statistical methods are applicable.	Graded similarity as a base of fuzzy reasoning. Fuzzy IF-THEN rules. Constructing real world applications by means of multiple valued logic. Para consistent logic in solving decision making problems.
3.	Monoidal Logic as a basis of various non-standard logics: linear logic, intuitionistic logic, basic fuzzy logic, Lukasiewicz logic.	Residuated lattices, Girard monoids, Heyting algebras, BL-algebras, Wajsberg algebras and MV-algebras. Semantics, syntax and completeness of various non-standard logics.

Study material

Type	Name	Author	ISBN	URL	Edition, availability, ...	Examination material	Language
Book	Mathematics behind Fuzzy Logic	Esko Turunen	3-7908-1221-8		Springer-Verlag, 1999, ISBN 3-7908-1221-8		English
Other online content	LISpMiner	Jan Rauch					English
Online book	Mechanizing hypothesis formation	Hajek, P., Havranek, T.					English

Correspondence of content

Additional information

The course is composed of three separate topics that can be studied independently from each other. The parts are: I Data mining - the GUHA method. II Fuzzy logic - theory and applications. III Many-valued logics.

More precise information per implementation

	Description	Methods of instruction	Implementation
Implementation 1		Lectures Excercises Laboratory assignments	Contact teaching: 0 % Distance learning: 0 % Self-directed learning: 0 %

Last modified	13.03.2009
Modifier	Esko Turunen