Igor Mashechkin

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In the paper, the most state-of-the-art methods of automatic text summarization, which build summaries in the form of generic extracts, are considered. The original text is represented in the form of a numerical matrix. Matrix columns correspond to text sentences, and each sentence is represented in the form of a vector in the term space. Further, latent(More)
This paper presents a new generic text summarization method using Non-negative Matrix Factorization (NMF) to estimate sentence relevance. Proposed sentence relevance estimation is based on normalization of NMF topic space and further weighting of each topic using sentences representation in topic space. The proposed method shows better summarization quality(More)
Nowadays there is a growing interest to active authentication methods in security society. These methods are used for user identity validation with behavioral biometrics such as keystroke or mouse moving dynamics. In this article a new hybrid method for active authentication using keystroke dynamics is presented. This method is a combination of a new(More)
This paper presents a new generic text summarization method using Non-negative Matrix Factorization (NMF) to estimate sentence relevance. Proposed sentence relevance estimation is based on normalization of NMF topic space and further weighting of each topic using sentences representation in topic space. The proposed method shows better summarization quality(More)
In the paper we describe the NMF-based approach applied to the problem of determining an employee's access needs. The conducted research showed that the proposed NMF-based methods provide a useful analytical framework for processing and modeling employee's access needs data, and the obtained results demonstrate acceptable performance and provide descriptive(More)
Spam-detection systems based on traditional methods have several obvious disadvantages like low detection rate, necessity of regular knowledge bases’ updates, impersonal filtering rules. New intelligent methods for spam detection, which use statistical and machine learning algorithms, solve these problems successfully. But these methods are not widespread(More)
Currently, the greatest risks for information security of organizations are internal, rather than external, threats. Data loss prevention (DLP) systems are used for minimization of risks related to internal threats. The main function of the DLP systems is to prevent leak of confidential data; however, comparison of the DLP systems relies currently on their(More)