is a theory of data analysis, which identifies conceptual structures among data sets; Rudolf Wille introduced it in 1982. It structures data into units that are formal abstractions of concepts of human thought, allowing meaningful and comprehensible interpretation. FCA models the world as being composed of objects and attributes. A strong feature of FCA is its capability of producing graphical visualizations of the inherent structures among data. In the field of information science there is a further application: the mathematical lattices that are used in FCA can be interpreted as classification systems. Formalized classification systems can be analyzed according to the consistency of their relations. (FAC Home Page r).
Published in Chapter:
Principles on Symbolic Data Analysis
Héctor Oscar Nigro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina) and Sandra Elizabeth González Císaro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)
Copyright: © 2009
|Pages: 8
DOI: 10.4018/978-1-60566-242-8.ch009
Abstract
Today’s technology allows storing vast quantities of information from different sources in nature. This information has missing values, nulls, internal variation, taxonomies, and rules. We need a new type of data analysis that allows us represent the complexity of reality, maintaining the internal variation and structure (Diday, 2003). In Data Analysis Process or Data Mining, it is necessary to know the nature of null values - the cases are by absence value, null value or default value -, being also possible and valid to have some imprecision, due to differential semantic in a concept, diverse sources, linguistic imprecision, element resumed in Database, human errors, etc (Chavent, 1997). So, we need a conceptual support to manipulate these types of situations. As we are going to see below, Symbolic Data Analysis (SDA) is a new issue based on a strong conceptual model called Symbolic Object (SO). A “SO” is defined by its “intent” which contains a way to find its “extent”. For instance, the description of habitants in a region and the way of allocating an individual to this region is called “intent”, the set of individuals, which satisfies this intent, is called “extent” (Diday 2003). For this type of analysis, different experts are needed, each one giving their concepts.