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Generalizations that handle incomplete, faulty, orimprecise data are discussed, but the focus lies on knowledge extraction from areliable information source.The method is based on... Læs mere
This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today.
Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the University of Hong Kong and the Oxford University Computing Laboratory, University of Oxford.
The workshop proceedings provide opportunities for delegates to discuss the latest research in TEL (Technology Enhanced Learning) and its impacts for learners and institutions, using cloud technologies.
This book reviews forecasting data mining models, from basic tools for stable data through causal models, to more advanced models using trends and cycles. These models are... Læs mere
Chapter 2 covers data visualization, including directions for accessing R open source software (described through Rattle). Chapter 7 goes on to describe link analysis, social... Læs mere
This textbook, “Exploratory Data Analysis in Business and Economics”, aims to familiarise students of economics and business as well as practitioners in firms with the basic principles, techniques, and applications of descriptive statistics and data analysis.
This book constitutes the refereed proceedings of the 7th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2013, held in Guanacaste, Costa Rica, in December 2013.