BigData 2014 - Big Data: Algorithms, Analytics, and Applications

Big Data: Algorithms, Analytics, and Applications
(Chapman & Hall/CRC Big Data Series)
CRC Press, Taylor & Francis Group, USA
As data sets are being generated at exponential rate all over the world, Big Data has become an indispensable issue. While organizations are capturing exponentially larger amount of data than ever these days, they have to re-think about and figure out what to digest it. The implicit meaning of data can be interpreted in reality through novel and evolving algorithms, analytics techniques, and innovative and effective use of hardware and software platforms so that organizations can harness the data, discover hidden patterns, and use newly acquired knowledge to act meaningfully for competitive advantages.
This book intends to cover fundamental and realistic issues about Big Data, including efficient algorithmic methods to process data, better analytical strategies to digest data, and representative applications in diverse fields such as Medicine, Science and Engineering, seeking to bridge the gap between huge amount of data and appropriate computational methods for scientific and social discovery, and to bring technologies for media/data communication, elastic media/data storage, cross-network media/data fusion, SaaS, and others together. It also aims at interesting applications involving in Big Data.
Target Audience
This book can prove useful to researchers, professors, research students and practitioners, as it will report novel research work on challenging topics in the area of Cloud Computing and Digital Media. Researchers and professionals in Data Centers, Multimedia Storage, Indexing, Security, and Application Industry are also targets in the pool of potential readers.
Recommended Topics
Recommended topics include, but are not limited to, the following:
Big Data Capture
Big Data Representation
Database vs. Big Table (or key-value pair)
Storage for Big Data
Big Data Sharing and Transferring
Big Data Processing Architecture
Data Warehousing and OLAP over Big Data
Security and Privacy Aspects of Big Data
Big Data Analytic Algorithms
Cluster Analysis
Pattern Recognition
Machine Learning
Data/text/image Mining
Statistics
Big Data Visualization
Big Data Applications
Bioinformatics
Multimedia Industry
Social Computing
Engineering
Finance
Governance and Business
Additional Information
Inquiries and submissions can be forwarded electronically by email to bigdata-book-AT-googlegroups.com