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    Generalized formal model of Big Data
    (Commission of Motorization and Energetics in Agriculture, 2016) Shakhovska, N.; Veres, O.; Hirnyak, M.
    This article dwells on the basic characteristic features of the Big Data technologies. It is analyzed the existing definition of the “big data” term. The article proposes and describes the elements of the generalized formal model of big data. It is analyzed the peculiarities of the application of the proposed model components. It is described the fundamental differences between Big Data technology and business analytics. Big Data is supported by the distributed file system Google File System technology, Cassandra, HBase, Lustre and ZFS, by the MapReduce and Hadoop programming constructs and many other solutions. According to the experts, such as McKinsey Institute, the manufacturing, healthcare, trade, administration and control of individual movements undergo the transformations under the influence of the Big Data.
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    The method of automatic summarization from different sources
    (Commission of Motorization and Energetics in Agriculture, 2016) Shakhovska, N.; Cherna, T.
    In this article is analyzed technology of automatic text abstracting and annotation. The role of annotation in automatic search and classification for different scientific articles is described. The algorithm of summarization of natural language documents using the concept of importance coefficients is developed. Such concept allows considering the peculiarity of subject areas and topics that could be found in different kinds of documents. Method for generating abstracts of single document based on frequency analysis is developed. The recognition elements for unstructured text analysis are given. The method of pre-processing analysis of several documents is developed. This technique simultaneously considers both statistical approaches to abstracting and the importance of terms in a particular subject domain. The quality of generated abstract is evaluated. For the developed system there was conducted experts evaluation. It was held only for texts in Ukrainian. The developed system concluding essay has higher aggregate score on all criteria. The summarization system architecture is building. To build an information system model there is used CASE-tool AllFusion ERwin Data Modeler. The database scheme for information saving was built. The system is designed to work primarily with Ukrainian texts, which gives a significant advantage, since most modern systems still oriented to English texts.