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Towards an optimal task-driven information granulationстатья
- Автор: Alexander Ryjov
- Сборник: Information Granularity, Big Data, and Computational Intelligence. Ed. by Witold Pedrycz and Shyi-Ming Chen
- Серия: Studies in Big Data Series
- Том: 8
- Глава в коллективной монографии
- Год издания: 2014
- Место издания: Springer, Cham
- Первая страница: 191
- Последняя страница: 208
- DOI: 10.1007/978-3-319-08254-7_9
- Аннотация: In this work we have analyzed Big Data sources and made a conclusion that sizeable part of them is people-generated data. We can present this type of data in form of qualitative attributes. The model of such attributes is a collection of fuzzy granules. We also need to granulate the data for application of a big part of analytical technologies. When we form the granules, we have a choice among different variants. Which of them is good for specific task? How can we measure this “goodness” and make a choice the best (optimal) granulation? We provide our vision of answers on these questions in the chapter.
- Добавил в систему: Рыжов Александр Павлович