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2014 IEEE JAVA DATA MINING PROJECT Data mining with big data
1. GLOBALSOFT TECHNOLOGIES
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Data mining with big data
Abstract
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With
the fast development of networking, data storage, and the data collection capacity, Big Data are now
rapidly expanding in all science and engineering domains, including physical, biological and biomedical
sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution,
and proposes a Big Data processing model, from the data mining perspective. This data-driven model
involves demand-driven aggregation of information sources, mining and analysis, user interest
modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven
model and also in the Big Data revolution.
Existing system
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With
the fast development of networking, data storage, and the data collection capacity, Big Data are now
rapidly expanding in all science and engineering domains, including physical, biological and biomedical
sciences.
Proposed system
This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and
proposes a Big Data processing model, from the data mining perspective. This data-driven model
involves demand-driven aggregation of information sources, mining and analysis, user interest
modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven
model and also in the Big Data revolution.
2. SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 256 MB(min)
Hard Disk - 20 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
SOFTWARE CONFIGURATION:-
Operating System : Windows XP
Programming Language : JAVA
Java Version : JDK 1.6 & above.