Frontiers in Massive Data Analysis
Regular price
€46.99
Regular price
€47.99
Sale
Sale price
€46.99
14 days return policy
Shipping & Delivery
A01=Board on Mathematical Sciences and Their Applications
A01=Committee on Applied and Theoretical Statistics
A01=Committee on the Analysis of Massive Data
A01=Division on Engineering and Physical Sciences
A01=National Research Council
Age Group_Uncategorized
Age Group_Uncategorized
Author_Board on Mathematical Sciences and Their Applications
Author_Committee on Applied and Theoretical Statistics
Author_Committee on the Analysis of Massive Data
Author_Division on Engineering and Physical Sciences
Author_National Research Council
automatic-update
Category1=Non-Fiction
Category=PBT
Category=UNC
Category=UNF
COP=United States
Delivery_Delivery within 10-20 working days
eq_bestseller
eq_computing
eq_isMigrated=0
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Language_English
PA=Available
Price_€20 to €50
PS=Active
softlaunch
Product details
- ISBN 9780309287784
- Dimensions: 152 x 229mm
- Publication Date: 03 Sep 2013
- Publisher: National Academies Press
- Publication City/Country: US
- Product Form: Paperback
- Language: English
Secure
checkout
Fast Shipping
Easy returns
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale--terabytes and petabytes--is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore.
Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge--from computer science, statistics, machine learning, and application disciplines--that must be brought to bear to make useful inferences from massive data.
