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In the paper, we propose a method for mining real-estate listings using clustering algorithms intended for numerical data. The presented approach is based on information systems over ontological graphs. Such information systems have been proposed to deal with data in the form of concepts linked by different semantic relations. A special attention is focused on preprocessing steps transforming advertisements in the textual form into information systems defined over ontological graphs, as well as on encoding attribute values for clustering algorithms.

In this paper, we deal with the problem of the initial analysis of data from evaluation sheets of subjects with autism spectrum disorders (ASDs). In the research, we use an original evaluation sheet including questions about competencies grouped into 17 spheres. An initial analysis is focused on the data preprocessing step including the filtration of cases based on consistency factors. This approach enables us to obtain simpler classifiers in terms of their size (a number of nodes and leaves in decision trees and a number of classification rules).