ICFCA06 - Invited Lectures

 

 

 

Talk: Methods of Conceptual Knowledge Processing - Rudolf Wille (Technische Universität Darmstadt)

 

Abstract. The offered methods of Conceptual Knowledge Processing are procedures which are well-planed to mean and purpose and therewith lead to skills for solving practical tasks. The used means and skills have been mainly created as translations of mathematical means and skills of Formal Concept Analysis. Those transdisciplinary translations may be understood as transformations from mathematical thinking, dealing with potential realities, to logical thinking, dealing with actual realities. Each of the 38 presented methods is discussed in a general language of logical nature, while citations give links to the underlying mathematical background. Applications of the methods are demonstrated by concrete examples mostly taken from the literature to which explicit references are given.

 

 

Talk: An Enumeration Problem in Ordered Sets Leads to Possible Benchmarks for Run-Time Prediction Algorithms - Tushar S. Kulkarni, Bernd S. W. Schröder (Louisiana Tech University)

 

Abstract. Motivated by the desire to estimate the number of order-preserving self maps of an ordered set, we compare three algorithms (Simple Sampling, Partial Backtracking and Heuristic Sampling) which predict how many nodes of a search tree are visited. The comparison is for the original algorithms that apply to backtracking and for modifications that apply to forward checking. We identify generic tree types and concrete, natural problems on which the algorithms predict incorrectly. We show that incorrect predictions not only occur because of large statistical variations but also because of (perceived) systemic biases of the prediction. Moreover, the quality of the prediction depends on the order of the variables. Our observations give new benchmarks for estimation and seem to make heuristic sampling the estimation algorithm of choice.

 

 

Talk: Attribute Implications in a Fuzzy Setting - Radim Bělohlávek (Palacky University of Olomouc), Vilém Vychodil

 

Abstract. The paper is an overview of recent developments concerning attribute implications in a fuzzy setting. Attribute implications are formulas of the form A Þ B, where A and B are collections of attributes, which describe dependencies between attributes. Attribute implications are studied in several areas of computer science and mathematics. We focus on two of them, namely, formal concept analysis and databases.

 

Talk: The Assessment of Knowledge, in Theory and in Practice

Jean-Claude Falmagne, Eric Cosyn, Jean-Paul Doignon (Free University of Brussels), Nicolas Thiéry

 

Abstract. This paper is adapted from a book and many scholarly articles. It reviews the main ideas of a theory for the assessment of a student’s knowledge in a topic and gives details on a practical implementation in the form of a software. The basic concept of the theory is the ‘knowledge state,’ which is the complete set of problems that an individual is capable of solving in a particular topic, such as Arithmetic or Elementary Algebra. The task of the assessor - which is always a computer - consists in uncovering the particular state of the student being assessed, among all the feasible states. Even though the number of knowledge states for a topic may exceed several hundred thousand, these large numbers are well within the capacity of current home or school computers. The result of an assessment consists in two short lists of problems which may be labelled: ‘What the student can do’ and ‘What the student is ready to learn.’ In the most important applications of the theory, these two lists specify the exact knowledge state of the individual being assessed. Moreover, the family of feasible states is specified by two combinatorial axioms which are pedagogically sound from the standpoint of learning. The resulting mathematical structure is related to closure spaces and thus also to concept lattices. This work is presented against the contrasting background of common methods of assessing human competence through standardized tests providing numerical scores. The philosophy of these methods, and their scientific origin in nineteenth century physics, are briefly examined.