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О формализации понятий в анализе неструктурированной информации
С. 345–352.
Maysuradze A. I.
Maltseva S. V., Лазарев В. В., Информационные технологии в проектировании и производстве 2015 № 1 С. 62–67
Высокая скорость изменений в бизнесе и необходимость ориентации на потребителя делают критическими требования к скорости и точности решений, принимаемых на основе маркетинговой аналитики. Рассмотрены новые возможности, предоставляемые технологиями больших данных, позволяющие совершить качественный прорыв в этом направлении. Рассмотрены наиболее важные направления применения технологий больших данных в области маркетинговой аналитики для сферы электронной коммерции. Даны подробные ...
Added: May 25, 2015
Brykina M. M., Toldova S., Faynveyts A. V., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной Международной конференции «Диалог» (Бекасово, 29 мая - 2 июня 2013 г.). В 2-х т.Т. 1: Основная программа конференции. Вып. 12 (19).: М.: РГГУ, 2013. P. 163–177.
The Information Extraction task and the task of Named Entities recognition (NER) in unstructured texts in particular, are essential for modern Mass Media systems. The paper presents a case study of NER system for Russian. The system was built and tested on the Russian news texts. The method of ambiguity resolution under discussion is based ...
Added: February 13, 2014
M.: Higher School of Economics Publishing House, 2011.
Concept discovery is a Knowledge Discovery in Databases (KDD) research field that uses human-centered techniques such as Formal Concept Analysis (FCA), Biclustering, Triclustering, Conceptual Graphs etc. for gaining insight into the underlying conceptual structure of the data. Traditional machine learning techniques are mainly focusing on structured data whereas most data available resides in unstructured, often ...
Added: December 3, 2012
Gromoff A., Bilinkis (Stavenko) J., Kazantsev N., , in: EDULEARN12 4th International Conference on Education and New Learning Technologies Publications.: Barcelona: International Association of Technology, Education and Development , 2012. P. 1236–1243.
This article describes the application of currently most promising methods of (1) network (graph) theory, (2) content analysis and (3) subject-oriented approach to business process modeling for creating and automation of innovative process and therefore for maximization of ROI (return on investments) in intellectual and social capital of enterprises. Described approach delivers opportunities for unstructured ...
Added: September 19, 2012
Gromoff A., Bilinkis (Stavenko) J., Kazantsev N., , in: Proceedings of Modeling, Simulation, verification and validation of enterprise information systems and web intelligence.: Wrocław: ICEIS, 2012. P. 94–105.
This article describes the application of currently most promising methods of (1) network (graph) theory, (2) content analysis and (3) subject-oriented approach to business process modelling for creating and automation of innovative process and therefore for maximization of ROI (return on investments) in intellectual and social capital of enterprises.
Described approach delivers opportunities for unstructured information ...
Added: September 14, 2012