Vestnik On-line
Orenburg State University december 07, 2021   RU/EN
Headings of Vestnik
Pedagogics
Psychology
Other

Search
Vak
Антиплагиат
Orcid
Viniti
ЭБС Лань
Rsl
Лицензия Creative Commons

2013, № 11 (160)



Soloviev N.A., Chernoprudova E.N. FORMATION OF COLLOCATIONS IN THE PROBLEM CONTENT E-MAIL FILTERINGThe problems of stable combinations in formation the problem — spam e-mail messages. The solution of the problem on the basis of pre-processing semantic text messages for use of neural network classifier. The technique of forming stable combinations, is grounded in the content analysis for the formation of a thesaurus system to protect postal services business correspondence.Key words: e-mail messages, the semantics of the text, content analysis, set phrases, intelligent processing, spam, content filtering.

Download
References:

1 Nikolaev, I. A. Spam: economic loss [Electronic resource]: analytical report / I. A. Nikolaev, M. V. Titova. — Mode of access: http://www.fbk.ru/news/5419/83743/.

2 Slepov, O. Content filtering [Electronic resource] / O. Slepov // JetInfo. — 2005. — №10 (149). — Mode of access: http://www.jetinfo.ru/Sites/new/Uploads/ 2005_10.pdf.

3 Soloviev, N. A. Development of the concept of intrusion detection / N. A. Soloviev, E. N. Chernoprudova // Modern information technologies in science, education and practice: proceedings of the VIII vseros. nauch.-practical. Conf., / Orenburg. state University. — Orenburg, 2009. — P. 66-67. — ISBN 978-5-7410-0975-8.

3 Chernoprudova, E. N. Neural network model of intellectual filtering unauthorized mailings / E. N. Chernoprudova // Information Materials of the IX all-Russian scientific-practical conference. — Orenburg, 2010. — P. 44-47.

4 Chernoprudova, E. N. Intelligent filtering unauthorized mailings based on the neural network / E. N. Chernoprudova, N. A. Soloviev // Intellect. Innovations. Investments. — 2011. — Specials. vol. — P.106-107.

5 McCallum, A. A comparison of Event Models for Naive Bayes Text Classifiection / A. McCallum, K. Nigam // AAAI-98 Workshop on Learning for Text Categorization. — Madison, 1998. — 8 c.

6 Fuernkranz, J. A study using n-gram Features for Text Categorization / J. Fuernkranz // Technical Report OEFAI-TR-98-30, Austrian Research Institute for Artificial Intelligence, Wien, Austria, 1998.

7 Dasigi, V. Neural Net Learning Issues in Classification of Free Text Documents / V. Dasigi, R. Manu // AAAI spring symposium on Machine Learning in Information Access — 1996.

8 Li, Y. H. Classification of Text Documents /Y. H. Li, A. K. Jain // The Computer Journal. — 1998. — Vol. 41, №8. — P. 537-546.

9 Mingyong, L. An improvement of TFIDF weighting in text categorization [Electronic resource] / L. Mingyong, Y. Jiangang. — Mode of access: http:// www.ipcsit.com/vol47/009-ICCTS2012-T049.pdf.

10 Cover, T. Elements of Information theory [Electronic resource] / T. Cover, J. Thomas. — Mode of access: https:// web.cse.msu.edu/cse842/Papers/CoverThomas-Ch2.pdf.

11 Kondratiev, M. E. Two-level hierarchical clustering news flow in ROMIP 2006 [Electronic resource] / M. E. Kondratiev // Russian workshop on the assessment of the methods of information search: Tr. fourth grew. seminar ROMIP'2006. — Saint-Petersburg, 2006. — P. 126-138. — Mode of access: http://romip.narod.ru/ romip2006/index.html.

12 Hotho, A. Ontology-based Text Clustering / A. Hotho, S. Staab, A. Maedche [Electronic resource] — Mode of access: http://www.cs.cmu.edu/mccallum/ textbeyond/papers/hotho.pdf

13 Lan, M. Supervised and Traditional Term Weighting Methods for Automatic Text Categorization / M. Lan, C. L. Tan, Senior Member [ Electronic resource] — Mode of access: https://www-old.comp.nus.edu.sg/ ~ tancl/publications/ j2009/PAMI2007-v3.pdf

14 Manning, C. D. Introduction to information retrieval / K. D. Manning, P. Raghavan, N. Shutce. — Moscow: Williams, 2011. — 528 p.

15 Yagunova, E. V. collocation method for structures / E. V. Yagunova, L. M Pivovarov // The Russian language: structural and lexical-semantic approaches / resp. amended by S. S. Sai. — Saint-Petersburg, 2011. — P. 137.

16 Khokhlova, M. V. Century Experimental testing methods for the isolation of the collocation method [Electronic resource] / M. V. Khokhlova. — Mode of access: http://www.helsinki.fi/slavicahelsingiensia/preview/sh34/pdf/21.pdf.

17 Theory of statistics textbook.-method. complex / V. G. Minashkin [and other] ; INTL. consortium "E-University", Moscow state University of Economics, statistics and Informatics, Eurasian open Institute. — Moscow: Izd. centre EOI, 2008. — 296 C. — ISBN 978-5-374-00041-2.

18 Khaikin, S. Neural networks: a comprehensive course / S. Khaikin. — Moscow: Williams, 2006. — 1104 p.

19 Valeev, C. C. Multi-level anti-spam filtering system based on artificial intelligence technologies / S. S. Valeev, A. P. Nikitin // Bulletin of USATU. — 2008. — 11, №1 (28). — P. 215-219.

20 Ginzburg EL Idioglossy: problems of identifying and learning context / E. Ginzburg / / The semantics of linguistic units: Reports of the VI International Conference. T-1, Moscow, 1998. — S. 26-28.


About this article

Authors: Solovyev N.A., Chernoprudova E.N.

Year: 2013


Editor-in-chief
Sergey Aleksandrovich
MIROSHNIKOV

Crossref
Cyberleninka
Doi
Europeanlibrary
Googleacademy
scienceindex
worldcat
© Электронное периодическое издание: ВЕСТНИК ОГУ on-line (VESTNIK OSU on-line), ISSN on-line 1814-6465
Зарегистрировано в Федеральной службе по надзору в сфере связи, информационных технологий и массовых коммуникаций
Свидетельство о регистрации СМИ: Эл № ФС77-37678 от 29 сентября 2009 г.
Учредитель: Оренбургский государственный университет (ОГУ)
Главный редактор: С.А. Мирошников
Адрес редакции: 460018, г. Оренбург, проспект Победы, д. 13, к. 2335
Тел./факс: (3532)37-27-78 E-mail: vestnik@mail.osu.ru
1999–2021 © CIT OSU