СПИСОК ИСПОЛЬЗОВАННЫХ ИСТОЧНИКОВ

[1] И. А. Чубукова. Data mining. Учебный курс. http://lnfm1.sai.msu.ru/~rastor/Books/Chubukova-Data_Mining.pdf

[2] Р.Г. Степанов. Технология Data Mining: Интеллектуальный Анализ Данных. Учебное пособие. ГОУ ВПО «Казанский Государственный Университет им. В.И.Ульянова-Ленина», Казань, 2008.

[3] Raymond Lam "Discovering Association Rules in Data Mining" http://www.raymond-lam.com/CS411.doc

[4] А. Павленко. Лекции по анализу данных. 2012 http://share.auditory.ru/2012/Artem.Pavlenko/%D0%BB%D0%B5%D0%BA%D1%86%D0%B8%D0%B8_%D0%B0%D0%B4.pdf

[5] http://www.basegroup.ru/library/analysis/association_rules/intro/

[6] R. Srikant, R. Agrawal. "Mining Generalized Association Rules", In Proc. of the 21th International Conference on VLDB, Zurich, Switzerland, 1995.

[7] R. Agrawal, R. Srikant. "Fast Discovery of Association Rules", In Proc. of the 20th International Conference on VLDB, Santiago, Chile, September 1994.

[8] В. И. Городецкий, В. В. Самойлов, “Ассоциативный и причинный анализ и ассоциативные байесовские сети”, Тр. СПИИРАН, 9 (2009), 13–65.

[9] R. Srikant, R. Agrawal. "Mining quantitative association rules in large relational tables". In Proceedings of the ACM SIGMOD Conference on Management of Data, Montreal, Canada, June 1996.

[10] Лаура Ирина Русу. Интеллектуальный анализ XML-данных: Часть 2. Поиск ассоциативных правил в XML-данных. http://www.ibm.com/developerworks/ru/library/x-datamine2/index.html

[11] R. Agrawal, T. Imielinski, A. Swami. Mining Associations between Sets of Items in Massive Databases. Proc. of the ACM-SIGMOD 1993 Int'l Conference on Management of Data, Washington D.C., May 1993

[12] J.S. Park, M.-S. Chen, and S.Y. Philip, "An Effective HashBased Algorithm for Mining Association Rules", In Proc. ACM SIGMOD Int’l Conf. Management of Data, ACM Press, New York, 1995.

[13] A. Savasere, E. Omiecinski, and S. Navathe, "An Efficient Algorithm for Mining Association Rules in Large Databases", In Proc. 21st Int’l Conf. Very Large Data Bases, Morgan Kaufmann, San Francisco, 1995.

[14] S. Brin et al., "Dynamic Itemset Counting and Implication Rules for Market Basket Data", In Proc. ACM SIGMOD Int’l Conf. Management of Data, ACM Press, New York, 1997.

[15] Zaki, Mohammed J.; Scalable algorithms for association mining, IEEE Transactions on Knowledge and Data Engineering, 12(3):372-390, May/June 2000.

[16] Han, Jiawei; Pei, Jian; Yin, Yiwen; and Mao, Runying; Mining frequent patterns without candidate generation, Data Mining and Knowledge Discovery 8:53-87, 2004.  

[17] Webb, Geoffrey I. (2000); Efficient Search for Association Rules, in Ramakrishnan, Raghu; and Stolfo, Sal; eds.; Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2000), Boston, MA, New York, NY: The Association for Computing Machinery, pp. 99-107.

[18] J. Mata, J. L. Alvarez, J. C. Riquelme: Evolutionary computing and optimization: An evolutionary algorithm to discover numeric association rules Proceedings of the 2002 ACM symposium on Applied computing. March 2002.

[19] M. J. Zaki, M. Ogihara, S. Parthasarathy, W. Li: Parallel data mining for association rules on shared-memory multi-processors Proceedings of the 1996 ACM/IEEE conference on Supercomputing (CDROM) Supercomputing '96. November 1996.

[20] Eui-Hong (Sam) Han, George Karypis, V. Kumar: Scalable Parallel Data Mining for Association Rules. Transaction on Knowledge and Data Engineering, 12(3): P. 728-737. 2000.

[21] http://www.basegroup.ru/library/analysis/association_rules/fpg/

[22] H. Toivonen, «Sampling Large Databases for Association Rules», Proc. 22nd Int?l Conf. Very Large Data Bases, Morgan Kaufmann, San Francisco, 1996, pp. 134-145.

[23] Ming-Syan Chen, Jiawei Han, Philip S. Yu: Data Mining: An Overview from a Database Perspective. IEEE Trans. On Knowledge And Data Engineering. 1996

[24] http://www.kdnuggets.com/polls/2012/analytics-data-mining-big-data-software.html

[25] KNIME Beginner's Luck : A Guide to KNIME Data Mining Software for Beginners. KNIME-Press, http://www.knime.org/knimepress/beginners-luck.

[26] The KNIME Cookbook : Recipes for the Advanced User. KNIME-Press, http://www.knime.org/knimepress/the-knime-cookbook.

[27] Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data, by Berthold, M.R., Borgelt, C., Höppner, F., Klawonn, F. Series: Texts in Computer Science Springer Verlag, 1st Edition., 2010.

[28] Christian Hidber, Online Association Rule Mining, SIGMOD 1999, Proceedings. ACM SIGMOD International Conference on Management of Data, June 1-3, 1999, Philadephia, Pennsylvania, pp.145-156.