Multi-source data fusion for economic data analysis

Data-Mining as Tool of Multimodal Business-Analysis: Lexical Transformation in Annual Reports of Rostech Corporation

The goal of the research is to study tools of Data Mining to find latent nature of lexical transformation in annual reports of the state-owned corporation ‘Rosteck’ and to estimate perspectives of extending methodology of businessanalysis by tools of multimodal business-analysis. Identification of trends in vocabulary transformation in annual reports was done by finding indicator features of unique key lexical units and their contexts. The author used methods of multimodal business-analysis and tools of Data Mining to study corporate reports in order to identify the most important signs and trends in business-vocabulary transformation at enterprises and corporations, which is usually ignored by conventional business-analysis. Russian texts of annual reports of ‘Rosteck’ corporation for 2017– 2021 act as initial data for the research. As Data Mining tools the author used Workflow-model on the on-line platform for analysis and data visualization Orange Data Mining 3.3.2. The research showed a clear trend to renewal of the annual report content within the period of analysis. Such units as ‘работник’ (worker), ‘обучение’ (training), ‘платформа’ (platform), ‘трансформация’ (transformation), ‘инициатива’ (initiative) and ‘академия’ (academy) demonstrated maximum dynamics in frequency growth. Context analysis allowed the author to draw a conclusion that transformation in business vocabulary is based on the growing attention of the corporation to problems of digital transformation, development of digital platforms, realization of technological and socio-humanitarian strategic initiatives, raising the quality of workers’ qualification by training in corporate net academy. Implementation of these measures requires upgrading strategy of managing finance, corruption, market and other risks. Multimodal business-analysis is a promising trend in academic research and a tool for resolving applied economic and organizational-managerial problems.

Information Quality Assessment for Data Fusion Systems

This paper provides a comprehensive description of the current literature on data fusion, with an emphasis on Information Quality (IQ) and performance evaluation. This literature review highlights recent studies that reveal existing gaps, the need to find a synergy between data fusion and IQ, several research issues, and the challenges and pitfalls in this field. First, the main models, frameworks, architectures, algorithms, solutions, problems, and requirements are analyzed. Second, a general data fusion engineering process is presented to show how complex it is to design a framework for a specific application. Third, an IQ approach, as well as the different methodologies and frameworks used to assess IQ in information systems are addressed; in addition, data fusion systems are presented along with their related criteria. Furthermore, information on the context in data fusion systems and its IQ assessment are discussed. Subsequently, the issue of data fusion systems’ performance is reviewed. Finally, some key aspects and concluding remarks are outlined, and some future lines of work are gathered.