The editorial Board of the journal "Russian Digital Libraries Journal" operates on the basis of Kazan (Volga) Federal University ( - one of the oldest educational institutions in Russia, which celebrated its 210th anniversary in 2014. Kazan University has always held leading positions in the domestic and international scientific and educational space, outstanding scientists and graduates of the University earned him international fame, and University culture has had a beneficial effect on the development of Kazan and the Volga region.

Current issue

Review of existing tools for detecting plagiarism and self-plagiarism
Annotation: All the time scientists need to publish the results of their work in order to remain relevant, meet the time, criteria, and not be outside the scientific community. The well-known principle of “publish or perish” often forces scientists to strive for quantity, not quality [1]. Along with the problems of authorship, paid research, the fabrication of the results, plagiarism and self-plagiarism are among the most common violations. Their impact is more subtle, but no less disruptive for the scientific community. The article provides an overview of the existing tools for identifying borrowing in the scientific articles of the authors. Decisions’ analysis is performed by com-paring systems for a number of characteristics. The tools are tested on real data to investigate their performance and efficiency.
Automation of android applications interactive prototypes development based on low-fidelity wireframes
Annotation: Some mechanisms for automation of Android applications interactive prototypes development based on handwritten wireframes are described in the paper. The process of automation includes machine learning methods used for the handwritten wireframes recognition. The mobile Android application is developed to ensure user interaction with these mechanisms.
Creating a comparison method for relational tables
Annotation: The article is devoted to creating a quick method of comparing a huge amount of data tables in relational database management systems. Creating an effective method for comparing relational systems is really relevant today. The study of existing solutions was conducted. The algorithm in this article was created using the probabilistic data structure «Countable Bloom filter» and the Monte Carlo Method. The proposed solution is unique in its direction, as it uses the least amount of temporary resources. A probabilistic model of the created algorithm is constructed, this algorithm can be used for parallelization.

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