ELECTRONIC SPAM FILTERING BASED ON NEURAL NETWORKS

Authors

Tulkun Fayzievich Bekmuratov, SIC ICT of TUIT, Tashkent, Uzbekistan, E-mail: bek.tulkun@yandex.ru, Phone: +998 71 234 07 92;Follow
Fayzullajon Bakhtiyorovich Botirov, post graduate of TUIT named after Mukhammad al-Khorazmy, Tashkent, Uzbekistan, Phone: (+998) 97 751-16-97(m.),Follow
Elshod Dilshod ugli Haydarov, TUIT named after Muhammad al-Khwarizmi, Tashkent, Uzbekistan, E-mail: elshodhaydarov1881@gmail.com, Phone: +998 97 306 99 95Follow

Abstract

This article analyzes the problem of filtering spam messages and addressing spam messages, Bayesian theorems based on artificial intelligence, LVQ algorithms (LVQ learning vector quantization) and a filtering scheme for systems based on neural networks. The direct construction of an effective neural network model of spam filtering using database recognition technology is considered. The parameters of access to the neural network how to include predefined statistical and non-statistical attributes of messages are given. The structure of neural network technology for classifying emails is also considered. The procedure for analyzing incoming data using the tool included in the analytical platform Deductor Studio 5.3 is described. as a result, a training kit is obtained that is suitable for use.

First Page

59

Last Page

65

References

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Recommended Citation

Bekmuratov, Tulkun Fayzievich; Botirov, Fayzullajon Bakhtiyorovich; and Haydarov, Elshod Dilshod ugli (2020) "ELECTRONIC SPAM FILTERING BASED ON NEURAL NETWORKS," Chemical Technology, Control and Management: Vol. 2020: Iss. 3, Article 10.
DOI: https://doi.org/10.34920/2020.3.59-65