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Development and Analysis of a Methodology for Automatic Detection of Evolution in a Domain Conceptual Model

Student: Nikolay Tyukaev

Supervisor: Eduard Babkin

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Business Informatics (Master)

Year of Graduation: 2020

The objective of this work is to reduce risks in project planning by identification and accurate assessment of the prospects of newly emerging trends and technologies. In this scientific work, the task is to consider linguistic engineering methods for analyzing a poorly structured array of text data and identifying trends in the planning and organization of activities of companies of industries. The hypothesis of the study is that the textual analysis of the final qualification works of students is an effective way to predict trends for high-quality strategic planning. The paper reviews the most relevant theoretical materials and describes the most popular full-text search platforms and software components for extracting structured information from text data. Apache Solr is used to build a trend analysis model of the technologies used among students of the Higher School of Economics. This model tests the feasibility of applying linguistic engineering technologies for business, including for companies with large financial and time costs due to the lack of full coverage of information channels.

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