Developing an Application to Assess Compliance of Publications in English with Academic Style Using Machine Learning Methods

Student: Falaleeva Veronika

Faculty: Faculty of Economics, Management, and Business Informatics

Educational Programme: Software Engineering (Bachelor)

Year of Graduation: 2018

Existing solutions that help solve the problem of the lack of a software product for analyzing publications in English to assess compliance with the scientific style. were analyzed. Markers for solving the existing problem were described. The methods of machine learning were analyzed, some of them were selected, designed and developed: support vector method, logistic regression, decision tree method, neural networks, naive Bayesian method. The software product for checking of the compliance with the scientific style was designed, developed and tested. The technical task, the feasibility study was written, the risks of the project were identified.

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