A Review on Data Mining Algorithms in Cloud Environment

Mani Butwall, Shraddha Kumar

Abstract


Data and information are basis for
todays industrial and day to day applications
of almost every domain. The volume of data for
most of human friendly applications is generally
enormous in nature and thus it is mandatory to
scale them in pre-defined clusters based on their
properties. Data mining has always interested
the researchers to characterize the data and
is integrated in applications like: Statistics,
Machine Learning, Artificial Intelligence, pattern
recognition etc. Data mining applications can
derive much demographic information concerning
customers that was previously not known or
hidden in the data. We have recently seen an
increase in data mining techniques targeted to
such applications as fraud detection, identifying
criminal suspects, and prediction of potential
terrorists. By and large, data mining systems
that have been developed to data for clusters,
distributed clusters and grids have assumed
that the processors are the scarce resource, and
hence shared. When processors become available,
the data is moved to the processors. This paper
surveys some data mining methods in their actual
nature and modifications made in their algorithms
for better output in their performance.

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