Data mining approaches for intelligent e-social care decision support system

Abstract

Large-scale of multidimensional recognitions of emotional diagnosis of disabled persons often generate large amount of multidimensional data with complex recognition mechanisms. The problem is to reveal main components of diagnosis and to construct flexible decision making support system. Sensors can easily record primary data, however the recognition of abnormal situations, clusterization of emotional stages and resolution for certain type of diagnosis is oncoming issue for bio-robot constructors. This paper analyses the possibilities of integration of different knowledge representation techniques, especially data mining methods, for development of the reinforcement framework with multiple cooperative agents for recognition of the prediction criteria of diagnosis of emotional situation of disabled persons. The research results present further development of model of framework with integration of the evaluation of data mining methods for wheelchair type robots working in real time by providing movement support for disabled individuals.