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Introduction

In many applications we deal with huge amount of data

E.g. insurance company records

Data by itself are not useful to support decisions

E.g. can I make an insurance contract to this new customer or it is too risky?

Thus we need a set of methods to generate from a data set a “summary” that represent a conceptualization of the data set

E.g. what are similarities among different customers of an insurance company that divide them in different risk classes?

Age >25, City=Innsbruck => Low Risk

This is a common task that is needed in several domains to support data analysis

Analysis of children suffering from diabetes

Marketing analysis of store departments or supermarkets

Formal Concept Analysis is a technique that enables resolution of such problems

Speaker notes:

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