Инд. авторы:	Guskov A., Ryabko B., Zubkov A.
Заглавие:	Classification of scientific documents based on the compression methods
Библ. ссылка:	Guskov A., Ryabko B., Zubkov A. Classification of scientific documents based on the compression methods // Совместный выпуск по материалам международной научной конференции «Вычислительные и информационные технологии в науке, технике и образовании» (CITech-2015) (24-27 сентября 2015 года): Вычислительные технологии, т.20; Вестник КазНУ им. Аль-Фараби, Серия математика, механика и информатиа № 3 (86) / КазНУ им. аль-Фараби. - 2015. - Part I. - Алматы - Новосибирск. - P.140-144.
Внешние системы:	РИНЦ: 24199872;
Издано:	2015
Физ. характеристика:	с.140-144
Конференция:	Название: International Conference «Computational and Informational Technologies in Science, Engineering and Education» Аббревиатура: CITech-2015 Город: Алма-Ата Страна: Казахстан Даты проведения: 2015-09-24 - 2015-09-27 Ссылка: http://conf.nsc.ru/citech-2015
Цитирование:	1. Antopolskii A.B., Belozerov V.N., Markarova T.S., Dmitrieva E.Y. Establishing appropriate GRNTI rubrics for different classification systems of scientific and technical information // Nauchno-tehnicheskaja informacija. Serija 1: Organizacija i metodika informacionnoj raboty. 2015. No 3. PP. 3-18. (in Russian) 2. Shaburova N.N., Belozerov V.N. UDC classification system for the indexing of documents on physics of semiconductor // Nauchno-tehnicheskaja informacija. Serija 1: Organizacija i metodika informacionnoj raboty. 2010. No 9. PP. 34-44. (in Russian) 3. Zaytseva E.M., Anisimova V.P. Digital versions of classification systems: history, current status and technological features // Nauchno-tehnicheskaja informacija. Serija 1: Organizacija i metodika informacionnoj raboty. 2015. No 1. PP. 29-34. (in Russian) 4. Barakhnin V.B., Nekhaeva V.A., Fedotov A.M. Prescription similarity measure for clustering text documents // Vestnik NGU. Serija: Informacionnye tehnologii. 2008. Vol. 6, No 1. PP. 3–9. (in Russian) 5. Barakhnin V.B., Tkachev D. A. Clustering of text documents based on the composite key terms // Vestnik NGU. Serija: Informacionnye tehnologii. 2010. Vol. 8. No 2. PP. 5–14. (in Russian) 6. Miao Y., Keselj V, Milios E. Document Clustering using Character N-grams: A Comparative Evaluation with Term-based and Word-based Clustering htps://web.cs.dal.ca/ eem/cvWeb/pubs/Miao-CIKM-2005.pdf 7. Baghel R., Dhir R. A Frequent Concepts Based Document Clustering Algorithm // International Journal of Computer Applications 2010 Vol. 4 No.5 C. 6– 12 8. Beil F., Ester M., Xu X. Frequent Term-Based Text Clustering //Proc. 8th Int. Conf. on Knowledge Discovery and Data Mining (KDD ’2002), Edmonton, Alberta, Canada, 2002. 9. Schaeffer, S.E. Graph clustering// Computer Science Review 2007 Vol.1 No.1, C. 27–64 10. Voronotsov K.V. Clustering algorithms and multidimensional scaling. Course of lectures. MSU, 2007 (in Russian) 11. Barsegyan A. A., Kupriyanov M. S., Stepanenko V. V., Kholod I.I. Data analysis technologies. Data Mining, Visual Mining, Text Mining, OLAP, BHV-Petersburg, 2007. (in Russian) 12. Rudi Cilibrasi and Paul M. B. Vitanyi. Clustering by Compression. IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, No. 4, 2005, pp. 1523 – 1545. 13. R. Cilibrasi, P. M. B. Vitanyi, and R. de Wolf, "Algorithmic clustering of music based on string compression Comp. Music J., vol. 28, no. 4, pp. 49–67, 2004. 14. Ryabko, B., Reznikova, Z., Druzyaka, A., Panteleeva, S. , Using Ideas of Kolmogorov Complexity for Studying Biological Texts. Theory of Computing Systems, Volume 52, Issue 1 (2013), Page 133–147. 15. Ryabko B.Y., Astola J., Malyutov M. Compression-Based Methods of Prediction and Statistical Analysis of Time Series: Theory and Applications. TICSP v.56. Tampere: Tampere International Center for Signal Processing. 2010. 110 p. http://ticsp.cs.tut.fi/images/8/89/Report-56.pdf 16. M. Li, P. M. B. Vitanyi. An Introduction to Kolmogorov Complexity and Its Applications, 2nd ed. New York: Springer-Verlag, 1997. 17. B. Ryabko, J. Astola, A. Gammerman. Application of Kolmogorov complexity and universal codes to identity testing and nonparametric testing of serial independence for time series. Theoretical Computer Science, v.359, pp.440–448, 2006.