Models, methods and algorithms for cyber-social computing and machine learning implies the use of the metric of similarity – difference of unitary coded information for processing big data in order… Click to show full abstract
Models, methods and algorithms for cyber-social computing and machine learning implies the use of the metric of similarity – difference of unitary coded information for processing big data in order to generate adequate actuator signals for controlling cyber-social critical systems. A set-theoretic method of data search is being developed based on the similarity – difference of the frequency parameters of primitive elements, which makes it possible to determine the similarity of objects, the strategy of transforming one object into another, and also to identify the level of common interests, conflicts. Computational architectures of cyber-social computing and metric search for key data are being created. The definitions of the fundamental concepts in the field of computing are given on the basis of metric relations between interacting processes and phenomena. A software application is proposed for calculating the similarity-differences of objects based on the formation of vectors of frequencies of two sets of primitive data. A high level of correlation of the application results with the well-known system for determining plagiarism is shown. Key words: computing, cybersocial computing, decision making, unitary data codes, similarity – difference, data retrieval, plagiarism
               
Click one of the above tabs to view related content.