國立虎尾科技大學 |

Big data analysis = new algorithms for a new society /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Big data analysis/ edited by Nathalie Japkowicz, Jerzy Stefanowski.
其他題名:	new algorithms for a new society /
其他作者:	Japkowicz, Nathalie.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	xii, 329 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Data mining. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-26989-4
ISBN:	9783319269894

Big data analysis = new algorithms for a new society /
Big data analysisnew algorithms for a new society /[electronic resource] :edited by Nathalie Japkowicz, Jerzy Stefanowski. - Cham :Springer International Publishing :2016. - xii, 329 p. :ill. (some col.), digital ;24 cm. - Studies in big data,v.162197-6503 ;. - Studies in big data ;v.1..

A Machine Learning Perspective on Big Data Analysis -- An Insight on Big Data Analytics -- Toward Problem Solving Support based on Big Data and Domain Knowledge: Interactive Granular Computing and Adaptive Judgment -- An overview of Conceptdrift Applications -- Analysis of Text-Enriched Heterogeneous Information Networks -- Implementing Big Data Analytics Projects in Business -- Data mining in Business: Current Advances and Future Challenges -- Industrial-Scale Ad Hoc Risk Analytics Using MapReduce -- Big Data and the Internet of Things -- Social Network Analysis in Streaming Call Graphs -- Scalable Cloud-Based Data Analysis Software Systems for Big Data From Next Generation Sequencing -- Discovering Networks of Interdependent Features in High-Dimensional Problems -- Final Remarks on Big Data Analysis and its Impact on Society and Science.

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.

ISBN: 9783319269894

Standard No.: 10.1007/978-3-319-26989-4doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

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505 0 $a A Machine Learning Perspective on Big Data Analysis -- An Insight on Big Data Analytics -- Toward Problem Solving Support based on Big Data and Domain Knowledge: Interactive Granular Computing and Adaptive Judgment -- An overview of Conceptdrift Applications -- Analysis of Text-Enriched Heterogeneous Information Networks -- Implementing Big Data Analytics Projects in Business -- Data mining in Business: Current Advances and Future Challenges -- Industrial-Scale Ad Hoc Risk Analytics Using MapReduce -- Big Data and the Internet of Things -- Social Network Analysis in Streaming Call Graphs -- Scalable Cloud-Based Data Analysis Software Systems for Big Data From Next Generation Sequencing -- Discovering Networks of Interdependent Features in High-Dimensional Problems -- Final Remarks on Big Data Analysis and its Impact on Society and Science.
520 $a This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.
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