Seminar on Computational Learning and Adaptation

  Towards a general framework for data mining

Saso Dzeroski
Department of Knowledge Technologies
Jozef Stefan Institute
Ljubljana, Slovenia



In this talk, I will address the ambitious task of formulating a
general framework for data mining. To begin, I will discuss the
requirements that such a framework should fulfill: it should elegantly
handle different types of data, different data mining tasks, and
different types of patterns/models. I will also discuss data mining
languages and what they should support, such as the design and
implementation of data mining algorithms and their composition into
nontrivial multistep knowledge discovery scenarios relevant for
practical application. I will proceed by laying out some basic
concepts, starting with (structured) data and generalizations (e.g.,
patterns and models) and continuing with data mining tasks and basic
components of data mining algorithms (i.e., refinement operators,
distances, features, and kernels). Next, I will discuss how to use
these concepts to formulate constraint-based data mining tasks and
design generic data mining algorithms. Finally, I will discuss how
these components fit in the overall framework and, in particular, into
a language for data mining and knowledge discovery.

Date: THURSDAY, August 16th

Time: 4:15-5:30PM 

Place: Cordura 100

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