Review: This article reviews the problems of automatic processing of web content. Since the speed of obsolescence of information in the global network is very high, the problem of prompt extraction of the necessary data from the Internet becomes more urgent. The research focuses on the web resources that contain text, unadapted to the automated processing. The subject of the research is a set of software and methods. A particular attention is paid to the categorization of ads placed on specialized websites. The authors also review practical aspects of the development of a universal architecture of information-gathering systems. The following methods were used during this study: analytical review of the main principles of development of systems of automated information gathering and analysis of natural languages. For obtaining practice-oriented methods of synthesis and analysis results were used. A special contribution of the authors of the study is in developing an automated system for collecting, processing and classification of the information contained on the web-site. The novelty of the research is to use a new approach to solve this problem by taking into account the semantics and structure characteristic for specific sites. The main conclusions of the study are the applicability and effectiveness of the classification method for solving this problem.

Keywords: machine learning, web robots, information collection, classification system, web-sites categorization, text analisis, parsing, data processing, crawling, big data

References:
Liu H. and Milios, E. (2012), PROBABILISTIC MODELS FOR FOCUSED WEB CRAWLING. Computational Intelligence, 28: 289–328
Menshchikov A.A., Gatchin Yu.A. Metody obnaruzheniya avtomatizirovannogo sbora informatsii s veb-resursov // Kibernetika i programmirovanie. – 2015. – № 5. – S.136-157.
Razniewski Simon, and Werner Nutt. Long-term Optimization of Update Frequencies for Decaying Information // Proceedings of the 18th International Workshop on Web and Databases. ACM. – 2015.
Pant Gautam, and Padmini Srinivasan Learning to crawl: Comparing classification schemes // ACM Transactions on Information Systems (TOIS) 23.4 (2005): 430-462.
Kim Jin Young, et al. Characterizing web content, user interests, and search behavior by reading level and topic // Proceedings of the fifth ACM international conference on Web search and data mining. ACM, 2012.
Pautov K. G., Popov F. A. Informatsionnaya sistema analiza i tematicheskoy klassifikatsii veb-stranits na osnove metodov mashinnogo obucheniya // Sovremennye problemy nauki i obrazovaniya. 2012. №6.
Aggarwal Charu C., and ChengXiang Zhai. "A survey of text classification algorithms." Mining text data. Springer US, 2012. 163-222.
Chen, Yu, Wei-Ying Ma, and Hong-Jiang Zhang. "Detecting web page structure for adaptive viewing on small form factor devices." Proceedings of the 12th international conference on World Wide Web. ACM, 2003.
Ageev Mikhail Sergeevich, Dobrov Boris Viktorovich, Lukashevich Natal'ya Valentinovna Avtomaticheskaya rubrikatsiya tekstov: metody i problemy // Uchen. zap. Kazan. un-ta. Ser. Fiz.-matem. nauki. 2008. №4.
Eswaran Dhivya, Paul N. Bennett, and Joseph J. Pfeiffer III. "Modeling Website Topic Cohesion at Scale to Improve Webpage Classification." Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2015.
Martinez-Alvarez, Miguel et al. "Document Difficulty Framework for Semi-automatic Text Classification" DAWAK (2013).
Tripathi, Nandita, Michael Oakes, and Stefan Wermter. "A Scalable Meta-Classifier Combining Search and Classification Techniques for Multi-Level Text Categorization." International Journal of Computational Intelligence and Applications 14.04 (2015).
Morfologicheskiy analizator pymorphy [Elektronnyy resurs]. – Rezhim dostupa: https://pythonhosted.org/pymorphy/, svobodnyy (data obrashcheniya: 30.09.2016).
Menshchikov A.A. Metody obnaruzheniya avtomatizirovannogo sbora informatsii s veb-resursov // Al'manakh nauchnykh rabot molodykh uchenykh Universiteta ITMO-2016. – T. 3. – S. 230-232

References (transliteration):
Liu H. and Milios, E. (2012), PROBABILISTIC MODELS FOR FOCUSED WEB CRAWLING. Computational Intelligence, 28: 289–328
Menshchikov A.A., Gatchin Yu.A. Metody obnaruzheniya avtomatizirovannogo sbora informatsii s veb-resursov // Kibernetika i programmirovanie. – 2015. – № 5. – S.136-157.
Razniewski Simon, and Werner Nutt. Long-term Optimization of Update Frequencies for Decaying Information // Proceedings of the 18th International Workshop on Web and Databases. ACM. – 2015.
Pant Gautam, and Padmini Srinivasan Learning to crawl: Comparing classification schemes // ACM Transactions on Information Systems (TOIS) 23.4 (2005): 430-462.
Kim Jin Young, et al. Characterizing web content, user interests, and search behavior by reading level and topic // Proceedings of the fifth ACM international conference on Web search and data mining. ACM, 2012.
Pautov K. G., Popov F. A. Informatsionnaya sistema analiza i tematicheskoy klassifikatsii veb-stranits na osnove metodov mashinnogo obucheniya // Sovremennye problemy nauki i obrazovaniya. 2012. №6.
Aggarwal Charu C., and ChengXiang Zhai. "A survey of text classification algorithms." Mining text data. Springer US, 2012. 163-222.
Chen, Yu, Wei-Ying Ma, and Hong-Jiang Zhang. "Detecting web page structure for adaptive viewing on small form factor devices." Proceedings of the 12th international conference on World Wide Web. ACM, 2003.
Ageev Mikhail Sergeevich, Dobrov Boris Viktorovich, Lukashevich Natal'ya Valentinovna Avtomaticheskaya rubrikatsiya tekstov: metody i problemy // Uchen. zap. Kazan. un-ta. Ser. Fiz.-matem. nauki. 2008. №4.
Eswaran Dhivya, Paul N. Bennett, and Joseph J. Pfeiffer III. "Modeling Website Topic Cohesion at Scale to Improve Webpage Classification." Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2015.
Martinez-Alvarez, Miguel et al. "Document Difficulty Framework for Semi-automatic Text Classification" DAWAK (2013).
Tripathi, Nandita, Michael Oakes, and Stefan Wermter. "A Scalable Meta-Classifier Combining Search and Classification Techniques for Multi-Level Text Categorization." International Journal of Computational Intelligence and Applications 14.04 (2015).
Morfologicheskiy analizator pymorphy [Elektronnyy resurs]. – Rezhim dostupa: https://pythonhosted.org/pymorphy/, svobodnyy (data obrashcheniya: 30.09.2016).
Menshchikov A.A. Metody obnaruzheniya avtomatizirovannogo sbora informatsii s veb-resursov // Al'manakh nauchnykh rabot molodykh uchenykh Universiteta ITMO-2016. – T. 3. – S. 230-232

Review: The subject of the study is an automated functional state bioradiolokation control of pilot to ensure accountability of such an assessment in the process of operation of the aircraft in real time. The developed methods and algorithms of data processing for the first time enable the correct mathematical treatment of physiological signals that are not limited to the pilot motor activity in their registration by taking into account nonstationarity and intraspecific variability in processing signals. This, in turn, significantly increase the potential for non-contact monitoring of the status of the pilot. Methods used in the research: a systematic analysis, filtering radio signals, wavelet analysis, artificial neural networks, mathematical cybernetics, pattern recognition. The developed technique of monitoring of bioradiolokation of condition of pilot enables the diagnostics of dangerous (for reliable professional activity) states in terms of the activity of the cardiovascular and respiratory system. Implementing the results of the study provides the possibility of increasing the reliability of operation of aircraft through the use of non-contact monitoring of the state of flight personnel in order to improve the reliability of their professional activities and account evaluation of the current state circuits control the aircraft.

Keywords: medical informatics, mathematical cybernetics, loop control of the aircraft, artificial neural network, wavelet analysis of signals, bioradiolokation monitoring, monitoring of the state human, ergatic management system, pattern of signal, automated signal processing

References:
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Ushakov I.B., Bogomolov A.V., Kukushkin Yu.A. Psikhofiziologicheskie mekhanizmy formirovaniya i razvitiya funktsional'nykh sostoyaniy // Rossiyskiy fiziologicheskiy zhurnal im. I.M. Sechenova. 2014. T. 100. № 10. S. 1130-1137.
Ushakov I.B., Bogomolov A.V. Informatizatsiya programm personifitsirovannoy adaptatsionnoy meditsiny // Vestnik Rossiyskoy akademii meditsinskikh nauk. 2014. № 5-6. S. 124-128.
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Kukushkin Yu.A., Maystrov A.I., Bogomolov A.V. Metody approksimatsii ritmokardiogramm dlya rascheta otsenok spektral'nykh pokazateley variabel'nosti serdechnogo ritma // Meditsinskaya tekhnika. 2010. № 3. S. 15-30.
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Alekhin M.D., Anishchenko L.N., Zhuravlev A.V. Kratnomasshtabnyy veyvlet-analiz v formirovanii prostranstva priznakov dvigatel'nykh patternov bioradiolokatsionnogo signala // Radiotekhnika. 2011. № 11. S. 20-24.
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Alekhin M.D., Anishchenko L.N., Korchagina D.A. Metod bioradiolokatsii v analize peremeshcheniy grudnoy kletki pri spokoynom dykhanii // Biomeditsinskaya radioelektronika. 2009. № 10. S. 56-61.
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Alekhin M.D. Protsedura opredeleniya optimal'nykh parametrov veyvlet-preobrazovaniya i neyrosetevogo klassifikatora dlya raspoznavaniya patternov nestatsionarnykh bioradiolokatsionnykh signalov // Neyrokomp'yutery: razrabotka, primenenie. 2012. № 6. S. 46-54.
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References (transliteration):
Adzhemov S.S., Tereshonok M.V., Chirov D.S. Raspoznavanie vidov tsifrovoy modulyatsii radiosignalov s ispol'zovaniem neyronnykh setey // Vestnik Moskovskogo universiteta. Seriya 3: Fizika. Astronomiya. 2015. № 1. S. 23-28.
Ushakov I.B., Bogomolov A.V., Kukushkin Yu.A. Psikhofiziologicheskie mekhanizmy formirovaniya i razvitiya funktsional'nykh sostoyaniy // Rossiyskiy fiziologicheskiy zhurnal im. I.M. Sechenova. 2014. T. 100. № 10. S. 1130-1137.
Ushakov I.B., Bogomolov A.V. Informatizatsiya programm personifitsirovannoy adaptatsionnoy meditsiny // Vestnik Rossiyskoy akademii meditsinskikh nauk. 2014. № 5-6. S. 124-128.
Bogomolov A.V., Kukushkin Yu.A. Avtomatizatsiya personifitsirovannogo monitoringa usloviy truda // Avtomatizatsiya. Sovremennye tekhnologii. 2015. № 3. S. 6-8.
Kukushkin Yu.A., Bogomolov A.V., Ushakov I.B. Matematicheskoe obespechenie otsenivaniya sostoyaniya material'nykh sistem // Informatsionnye tekhnologii. 2004. № 7 (prilozhenie). 32 s.
Ushakov I.B., Vorona A.A., Kukushkin Yu.A., Bogomolov A.V. Apparatno-programmnye kompleksy dlya mediko-psikhologicheskogo obespecheniya kontrolya nadezhnosti professional'noy deyatel'nosti cheloveka v usloviyakh vysokogo riska vozniknoveniya chrezvychaynoy situatsii // Bezopasnost' zhiznedeyatel'nosti. 2004. № 3. S. 8.
Bogomolov A.V., Maystrov A.I. Modelirovanie ritmokardiograficheskikh signalov v chastotnoy oblasti // Dinamika slozhnykh sistem-XXI vek. 2009. № 1. S. 49.
Kukushkin Yu.A., Maystrov A.I., Bogomolov A.V. Metody approksimatsii ritmokardiogramm dlya rascheta otsenok spektral'nykh pokazateley variabel'nosti serdechnogo ritma // Meditsinskaya tekhnika. 2010. № 3. S. 15-30.
Alekhin M.D., Anishchenko L.N., Zhuravlev A.V. Metod klassifikatsii dykhatel'nykh patternov bioradiolokatsionnogo signala na osnove iskusstvennykh neyronnykh setey i veyvlet-analiza // Biomeditsinskaya radioelektronika. 2011. № 10. S. 57-64.
Alekhin M.D., Anishchenko L.N., Zhuravlev A.V. Kratnomasshtabnyy veyvlet-analiz v formirovanii prostranstva priznakov dvigatel'nykh patternov bioradiolokatsionnogo signala // Radiotekhnika. 2011. № 11. S. 20-24.
Kukushkin Yu.A., Bogomolov A.V. Metodika kolichestvennogo otsenivaniya funktsional'nykh sostoyaniy cheloveka // Biomeditsinskaya radioelektronika. 2001. № 2. S. 12.
Bogomolov A.V. Kontseptsiya matematicheskogo obespecheniya diagnostiki sostoyaniya cheloveka // Informatika i sistemy upravleniya. 2008. № 2 (16). S. 11-13.
Alekhin M.D., Anishchenko L.N., Zhuravlev A.V., D'yachenko A.I. Metody vzaimnogo korrelyatsionno-spektral'nogo analiza v sravnenii dannykh bioradiolokatsii i respiratornoy pletizmografii // Biomeditsinskaya radioelektronika. 2012. № 8. S. 3-10.
Bogomolov A.V., Maystrov A.I. Teoretiko-eksperimental'noe issledovanie skhodimosti otsenok spektral'nykh pokazateley variabel'nosti serdechnogo ritma cheloveka // Meditsinskaya tekhnika. 2009. № 2. S. 26-31.
Alekhin M.D., Anishchenko L.N., Korchagina D.A. Metod bioradiolokatsii v analize peremeshcheniy grudnoy kletki pri spokoynom dykhanii // Biomeditsinskaya radioelektronika. 2009. № 10. S. 56-61.
Maystrov A.I., Bogomolov A.V., Alekhin M.D. Tekhnologiya avtomatizirovannoy obrabotki uchastkov lokal'nykh nestatsionarnostey v ritmokardiograficheskikh signalakh // Vestnik novykh meditsinskikh tekhnologiy. Elektronnoe izdanie. 2012. № 1. S. 4.
Alekhin M.D. Protsedura opredeleniya optimal'nykh parametrov veyvlet-preobrazovaniya i neyrosetevogo klassifikatora dlya raspoznavaniya patternov nestatsionarnykh bioradiolokatsionnykh signalov // Neyrokomp'yutery: razrabotka, primenenie. 2012. № 6. S. 46-54.
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Stolyar V.P. Metodologicheskie osobennosti prognozirovaniya situatsionnoy meditsinskoy obstanovki // Trendy i upravlenie.-2015.-1.-C. 3-9. DOI: 10.7256/2307-9118.2015.1.14118.
Lushkin A.M. Tekhnologiya avtomatizirovannoy riskometrii funktsional'noy nadezhnosti operatora ergaticheskoy sistemy // Trendy i upravlenie.-2015.-1.-C. 78-86. DOI: 10.7256/2307-9118.2015.1.14117.
Vorob'ev A.A., Lagoyko O.S. Informatsionno-diagnosticheskie sistemy vstroennogo kontrolya sostoyaniya vozdushnykh sudov // Programmnye sistemy i vychislitel'nye metody.-2014.-4.-C. 437-445. DOI: 10.7256/2305-6061.2014.4.13995.
Stolyar V.P. Metodologicheskie osobennosti prognozirovaniya situatsionnoy meditsinskoy obstanovki // Trendy i upravlenie. - 2015. - 1. - C. 3 - 9. DOI: 10.7256/2307-9118.2015.1.14118.
Lushkin A.M. Tekhnologiya avtomatizirovannoy riskometrii funktsional'noy nadezhnosti operatora ergaticheskoy sistemy // Trendy i upravlenie. - 2015. - 1. - C. 78 - 86. DOI: 10.7256/2307-9118.2015.1.14117.
Vorob'ev A.A., Lagoyko O.S. Informatsionno-diagnosticheskie sistemy vstroennogo kontrolya sostoyaniya vozdushnykh sudov // Programmnye sistemy i vychislitel'nye metody. - 2014. - 4. - C. 437 - 445. DOI: 10.7256/2305-6061.2014.4.13995.
Solntsev V.I., Somov M.V., Skuratovskiy N.I. Avtomatizatsiya ergonomicheskikh ekspertiz sredstv zashchity ot shuma // Programmnye sistemy i vychislitel'nye metody. - 2014. - 4. - C. 446 - 455. DOI: 10.7256/2305-6061.2014.4.14054.
Esev A.A., Lagoyko O.S. Metodika avtomatizirovannoy obrabotki izobrazheniy v aviatsionnykh sistemakh vizual'nogo monitoringa vnekabinnoy obstanovki // Programmnye sistemy i vychislitel'nye metody. - 2015. - 1. - C. 79 - 88. DOI: 10.7256/2305-6061.2015.1.14304.

Review: The author studies the early stages of the software life cycle on the quality of which the quality of the result of software development essentially depends. An analysis of the experience of the practical application of the widely used waterfall (cascade), iterative and incremental models of software life cycle showed that they do not fully meet the needs of the practices. However, there is a possibility of the synthesis of a new model of the life cycle of software that combines all of these three models. The research methodology is based on the models of the software life cycle, structured systems analysis, software engineering, and information and logical modeling. The main conclusions of the study lies in the model of the software life cycle (for the stage of its development), presented in notation UML-diagrams, which consists of the stages of initiation of development, setting the increment, execution of the increment and completion of the development. Practical implementation of the developed model provides a reduction in the time required for software development and preparing the necessary project documentation.

Keywords: life cycle stages, structured systems analysis, software development, life cycle model, information and logical modeling, software engineering, program life cycle, software, software tools, system engineering

References:
Cockburn L. Using both incremental and iterative development // Cross Talk: the journal of defense software Engineering, №5, 2008. RR. 27-30.
Beck K. Test Driven Development: by example. Addison-Wesley Professional 2002. 252 p.
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Beck K. Embracing Change with Extreme Programming // Computer, № 32 (10), 1999. RR. 70-77.
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Shipilov V.V. Ob epimorfnom preobrazovanii mnogomernykh dannykh v zadachakh postroeniya slozhnykh tekhnicheskikh sistem // Voprosy teorii bezopasnosti i ustoychivosti sistem. 2014. № 16. S. 27-39.
Kharitonov V.V., Merezhko A.N., Esev A.A., Zykin A.P. Strukturnyy sistemnyy analiz protsessov upravleniya zatratami na letnye ispytaniya aviatsionnogo vooruzheniya i voennoy tekhniki // Izvestiya Instituta inzhenernoy fiziki. 2013. T. 2. № 28. S. 32-35.
Chirov D.S., Tereshonok M.V., Elsukov B.A. Metod i algoritmy optimizatsii tekhnicheskikh kharakteristik kompleksov radiomonitoringa // T-Comm: Telekommunikatsii i transport. 2014. T. 8. № 10. S. 88-92.
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Larman K., Baziliyu V. Iterativnaya i inkremental'naya razrabotka: kratkaya istoriya // Otkrytye sistemy. 2003. № 9. S. 43-53.
Maksimov I.B., Stolyar V.P., Bogomolov A.V. Prikladnaya teoriya informatsionnogo obespecheniya mediko-biologicheskikh issledovaniy. M.: Binom, 2013. 312 s.
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Esev A.A., Tkachuk A.V., Zykin A.P. Metodicheskoe obespechenie issledovaniya tekhnicheskogo urovnya obraztsov vooruzheniya i voennoy tekhniki // Dvoynye tekhnologii. 2014. № 1 (66). S. 59-64.
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Bruks F. Mificheskiy cheloveko-mesyats, ili Kak sozdayutsya programmnye sistemy. SPb.: Simvol-Plyus, 2010. 304 s.
Buch G. Ob'ektno-orientirovannyy analiz i proektirovanie s primerami prilozheniy. M.: Vil'yams. 2008. 720 s.
Bogomolov A.V., Chuykov D.S., Zaporozhskiy Yu.A. Sredstva obespecheniya bezopasnosti informatsii v sovremennykh avtomatizirovannykh sistemakh // Informatsionnye tekhnologii. 2003. № 1. S. 2.
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Bogomolov A.V., Zueva T.V., Chikova S.S., Golosovskiy M.S. Ekspertno–analiticheskoe obosnovanie prioritetnykh napravleniy sovershenstvovaniya sistemy preduprezhdeniya biologicheskikh terroristicheskikh aktov // Informatika i sistemy upravleniya. 2009. № 4. S. 134–136.
Larman S. Agile and Iterative Development: A Manager's Guide // Addison-Wesley, 2004. 27 r.
Royce W. Managing the Development of Large Software Systems// TRW, August 1970. RR. 328-338.
Kubasheva E.S., Gavrilov A.G. Metodika otsenki kachestva veb-prilozheniy // Programmnye sistemy i vychislitel'nye metody.-2013.-1.-C. 28-34. DOI: 10.7256/2305-6061.2013.01.2.
Katasev A.S., Emaletdinova L.Yu. Nechetko-produktsionnaya kaskadnaya model' diagnostiki sostoyaniya slozhnogo ob'ekta // Programmnye sistemy i vychislitel'nye metody.-2013.-1.-C. 69-81. DOI: 10.7256/2305-6061.2013.01.6.

References (transliteration):
Cockburn L. Using both incremental and iterative development // Cross Talk: the journal of defense software Engineering, №5, 2008. RR. 27-30.
Beck K. Test Driven Development: by example. Addison-Wesley Professional 2002. 252 p.
Brooks F. No Silver Bullet — Essence and Accident in Software Engineering // Proceedings of the IFIP Tenth World Computing Conference: 1069–1076. 1986.
Beck K. Embracing Change with Extreme Programming // Computer, № 32 (10), 1999. RR. 70-77.
Agile-manifest razrabotki programmnogo obespecheniya. [Elektronnyy resurs] URL: http://agilemanifesto.org/iso/ru/ (data obrashcheniya 24.12.2014).
Shipilov V.V., Sakharov O.V. Planirovanie variantov grupp ispolniteley dlya obespecheniya vypolneniya etapov proekta // Nelineynyy mir. 2014. T. 12. № 7. S. 84-86.
Shipilov V.V. Ob epimorfnom preobrazovanii mnogomernykh dannykh v zadachakh postroeniya slozhnykh tekhnicheskikh sistem // Voprosy teorii bezopasnosti i ustoychivosti sistem. 2014. № 16. S. 27-39.
Kharitonov V.V., Merezhko A.N., Esev A.A., Zykin A.P. Strukturnyy sistemnyy analiz protsessov upravleniya zatratami na letnye ispytaniya aviatsionnogo vooruzheniya i voennoy tekhniki // Izvestiya Instituta inzhenernoy fiziki. 2013. T. 2. № 28. S. 32-35.
Chirov D.S., Tereshonok M.V., Elsukov B.A. Metod i algoritmy optimizatsii tekhnicheskikh kharakteristik kompleksov radiomonitoringa // T-Comm: Telekommunikatsii i transport. 2014. T. 8. № 10. S. 88-92.
Severtsev N.A., Shipilov V.V. Modelirovanie protsessa upravleniya innovatsionnymi proektami organizatsiy v usloviyakh neopredelennosti // Voprosy teorii bezopasnosti i ustoychivosti sistem. 2014. № 16. S. 3-15.
Larman K., Baziliyu V. Iterativnaya i inkremental'naya razrabotka: kratkaya istoriya // Otkrytye sistemy. 2003. № 9. S. 43-53.
Maksimov I.B., Stolyar V.P., Bogomolov A.V. Prikladnaya teoriya informatsionnogo obespecheniya mediko-biologicheskikh issledovaniy. M.: Binom, 2013. 312 s.
Kulikov G.V., Sosnin Yu.V., Nepomnyashchikh A.V., Nashchekin P.A. Modelirovanie protsessa zashchity informatsii pri realizatsii nesanktsionirovannogo dostupa k ney // Vestnik komp'yuternykh i informatsionnykh tekhnologiy. 2014. № 4 (118). S. 45-51.
Kukushkin Yu.A., Bogomolov A.V., Ushakov I.B. Matematicheskoe obespechenie otsenivaniya sostoyaniya material'nykh sistem // Informatsionnye tekhnologii. 2004. № 7 (prilozhenie). 32 s.
Kon M. Scrum: gibkaya razrabotka PO = Succeeding with Agile: Software Development Using Scrum. M.: Vil'yams, 2011. 576 r.
Esev A.A., Tkachuk A.V., Zykin A.P. Metodicheskoe obespechenie issledovaniya tekhnicheskogo urovnya obraztsov vooruzheniya i voennoy tekhniki // Dvoynye tekhnologii. 2014. № 1 (66). S. 59-64.
Esev A.A., Merezhko A.N., Tkachuk A.V. Tekhnologiya kvalimetrii tekhnicheskogo urovnya slozhnykh sistem // Vestnik komp'yuternykh i informatsionnykh tekhnologiy. 2014. № 7 (121). S. 28-34.
Golosovskiy M.S., Shashin A.E. Tekhnologiya adaptivnogo sinteza sistemy testovogo kontrolya kachestva avtomatizirovannogo obucheniya // Materialy VIII mezhdunarodnoy nauchnoy konferentsii «Sistemnyy analiz v meditsine» (SAM 2014). Blagoveshchensk, 2014. S. 71-74.
Golosovskiy M.S. Model' zhiznennogo tsikla razrabotki programmnogo obespecheniya v ramkakh nauchno-issledovatel'skikh rabot // Avtomatizatsiya i sovremennye tekhnologii. 2014. № 1. S. 43-46.
Vinogradov A.N., Makarenkov S.A., Chirov D.S. Primenenie metodov data mining dlya formirovaniya bazy znaniy ekspertnoy sistemy klassifikatsii radiosignalov // T-Comm: Telekommunikatsii i transport. 2010. T. 4. № 11. S. 61-64.
Bruks F. Mificheskiy cheloveko-mesyats, ili Kak sozdayutsya programmnye sistemy. SPb.: Simvol-Plyus, 2010. 304 s.
Buch G. Ob'ektno-orientirovannyy analiz i proektirovanie s primerami prilozheniy. M.: Vil'yams. 2008. 720 s.
Bogomolov A.V., Chuykov D.S., Zaporozhskiy Yu.A. Sredstva obespecheniya bezopasnosti informatsii v sovremennykh avtomatizirovannykh sistemakh // Informatsionnye tekhnologii. 2003. № 1. S. 2.
Bogomolov A.V., Maystrov A.I. Tekhnologiya analiza sistemnykh prichinno-sledstvennykh svyazey na osnove diagramm Isikavy // Sistemnyy analiz v meditsine (SAM 2014): Materialy VIII mezhdunarodnoy nauchnoy konferentsii. Blagoveshchensk, 2014. S. 13-16.
Bogomolov A.V., Zueva T.V., Chikova S.S., Golosovskiy M.S. Ekspertno–analiticheskoe obosnovanie prioritetnykh napravleniy sovershenstvovaniya sistemy preduprezhdeniya biologicheskikh terroristicheskikh aktov // Informatika i sistemy upravleniya. 2009. № 4. S. 134–136.
Larman S. Agile and Iterative Development: A Manager's Guide // Addison-Wesley, 2004. 27 r.
Royce W. Managing the Development of Large Software Systems// TRW, August 1970. RR. 328-338.
Kubasheva E.S., Gavrilov A.G. Metodika otsenki kachestva veb-prilozheniy // Programmnye sistemy i vychislitel'nye metody.-2013.-1.-C. 28-34. DOI: 10.7256/2305-6061.2013.01.2.
Katasev A.S., Emaletdinova L.Yu. Nechetko-produktsionnaya kaskadnaya model' diagnostiki sostoyaniya slozhnogo ob'ekta // Programmnye sistemy i vychislitel'nye metody.-2013.-1.-C. 69-81. DOI: 10.7256/2305-6061.2013.01.6.

Review: the article presents a review of formal methods of text attribution. The problem of determining the authorship of texts is present in different field and is important for philologists, literary critics, historians, lawyers. In solving the problem of text attribution the main interest and the main complexity is in the analysis of syntactic, lexical/idiomatic and stylistic levels of text. In a sense, a narrower task is in the text sentiment-analysis (defining the tone of the text). Techniques for solving the task can be useful for identifying authorship of the text. Unfortunately, expert analysis of author’s style is complex and time consuming. It’s desirable to find new approaches, allowing at least partially automate experts’ work. Therefore the article pays special attention exactly to the formal methods of author’s identification and software implementation of such methods. Currently, algorithms of data compression, methods of mathematical statistics, probability theory, neural networks algorithms and cluster analysis algorithms are applied for text attribution. The article describes the most popular software systems for author’s style identification for Russian language. Author attempts to make a comparative analysis, identify features and drawbacks of the reviews approaches. Among the problems hindering researches in text attribution there are a problem of selecting linguostylistic parameters of the text and a problem of selecting sample texts. The author states that there is a need in further researches, aimed at finding new or improving existing methods of texts attribution, at finding new characteristics allowing to clearly separate author’s style, including cases of short texts and small number of sample texts.

Keywords: text attribution, defining authorship, formal text parameters, author’s style, text classification, machine learning, statistical analysis, computer linguistics, identification of author’s style, analysis of textual information

Contact information: Batura Tat’yana Viktorovna, 630090, Russia, Novosibirsk, prospekt Akademika Lavrent’eva, 6

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References (transliteration):
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Avtoref. dis. kand. tekh. nauk. Tomsk, 2010. 26 s.
2. Marusenko M.A. Atributsiya anonimnykh i psevdonimnykh literaturnykh proizvedeniy metodami teorii
raspoznavaniya obrazov. L.: LGU, 1990. 164 s.
3. Rodionova E.S. Metody atributsii khudozhestvennykh tekstov // Strukturnaya i prikladnaya lingvistika:
Mezhvuzovskiy sbornik. SPb.: SPbGU, 2008. Vyp. 7. S. 118–127.
4. Markov A.A. Ob odnom primenenii statisticheskogo metoda // Izvestiya Imperatorskoy Akademii nauk.
Ser. 6. 1916. T. 10, № 4. S. 239–242.
5. Fomenko V.P., Fomenko T.G. Avtorskiy invariant russkikh literaturnykh tekstov // Novaya khronologiya Gretsii:
Antichnost' v Crednevekov'e. M.: MGU, 1995. 422 s.
6. Khmelev D.V. Klassifikatsiya i razmetka tekstov s ispol'zovaniem metodov szhatiya dannykh // Vse o szhatii
dannykh, izobrazheniy i video. 2003. URL: http://compression.ru/download/articles/classif/intro.html
(data obrashcheniya: 17.04.2014)
7. Khmelev D.V. Raspoznavanie avtora teksta s ispol'zovaniem tsepey A.A. Markova // Vestnik MGU. Ser. 9:
Filologiya. 2000. №2. S. 115–126.
8. Kukushkina O.V., Polikarpov A.A, Khmelev D.V. Opredelenie avtorstva teksta s ispol'zovaniem bukvennoy
i grammaticheskoy informatsii // Problemy peredachi informatsii. M.: Nauka, 2001. T. 37. № 2. S. 96–108.
9. Shevelev O.G. Razrabotka i issledovanie algoritmov sravneniya stiley tekstovykh proizvedeniy: Avtoref.
dis. kand. tekh. nauk. Tomsk, 2006. 18 s.
10. Timashev A.N. Atributor // Tekstologiya. ru. 1999–2007. URL: http://www.textology.ru/atr_resum.html
(data obrashcheniya: 17.04.2014)
11. Informatsionnaya sistema «Statisticheskie metody analiza literaturnogo teksta». 2004. URL: http://smalt.
karelia.ru (data obrashcheniya: 16.04.2014) .
12. Rogov A.A., Sidorov Yu.V., Korol' A.V. Avtomatizirovannaya sistema obrabotki i analiza literaturnykh
tekstov SMALT // Trudy i materialy II-go Mezhdunarodnogo kongressa issledovateley russkogo yazyka
«Russkiy yazyk: istoricheskie sud'by i sovremennost'». M: MGU, 2004. S. 485–486.
13. Antiplagiat. 2005–2014. URL: http://www.antiplagiat.ru (data obrashcheniya: 16.04.2014)
14. Shevelev O.G. Metody avtomaticheskoy klassifikatsii tekstov na estestvennom yazyke: Uchebnoe posobie.
Tomsk: TML-Press, 2007. 144 s.
15. Romanov A.S., Meshcheryakov R.V. Identifikatsiya avtora teksta s pomoshch'yu apparata opornykh vektorov / A.S.
Romanov, R.V. Meshcheryakov // Komp'yuternaya lingvistika i intellektual'nye tekhnologii: Po materialam
ezhegodnoy Mezhdunarodnoy konferentsii «Dialog 2009». M.: RGGU, 2009. Vyp. 8, №15. S. 432–437.
16. Pang B., Lee L. Opinion mining and sentiment analysis // Foundations and Trends in Information Retrieval.
Vol. 2, No 1-2. 2008. P. 1–135.
17. Pazel'skaya A.G., Solov'ev A.N. Metod opredeleniya emotsiy v tekstakh na russkom yazyke // Komp'yuternaya
lingvistika i intellektual'nye tekhnologii: cb. nauchnykh statey. M.: Izd-vo RGGU, 2011. Vyp. 10, №17.
S. 510–522.
18. Yi J., Nasukawa T., Bunescu R., Niblack W. Sentiment analyzer: extracting sentiments about a given topic using
natural language processing techniques // Proc. of the Third IEEE International Conference on Data Mining
(ICDM 2003), 2003. P. 427–434.
19. Ostin Dzh. Slovo kak deystvie // Novoe v zarubezhnoy lingvistike. M.: Progress, 1986. Vyp. 17. S. 22–130.
20. Onlayn entsiklopediya «Krugosvet». 1997–2014. URL: http://www.krugosvet.ru/enc/gumanitarnye_nauki/lingvistika/
RECHEVO_AKT.html (data obrashcheniya: 15.04.2014)
21. Serl' Dzh. Chto takoe rechevoy akt? // Novoe v zarubezhnoy lingvistike. M., 1986. Vyp. 17. S. 151–169.