5 IMPORTANT FUTURE TRENDS IN DATA MINING
5 IMPORTANT FUTURE TRENDS IN DATA MINING
Data mining is one of the most widely used methods to
extract data from different sources and organize them for better usage. In
spite of having different commercial systems for data mining, a lot of
challenges come up when they are actually implemented. With rapid evolution in
the field of data mining, companies are expected to stay abreast with all the
new developments.
Complex algorithms form the basis for data mining as they
allow for data segmentation to identify various trends and patterns, detect variations,
and predict the probabilities of various events happening. The raw data may
come in both analog and digital format, and is inherently based on the source
of the data. Companies need to keep track of the latest data mining trends and
stay updated to do well in the industry and overcome challenging competition.
5
Important Future Trends in Data Mining
Businesses
which have been slow in adopting the process of data mining are now catching up
with the others. Extracting important information through the process of data
mining is widely used to make critical business decisions. In the coming
decade, we can expect data mining to become as ubiquitous as some of the more
prevalent technologies used today.
1.
Multimedia Data Mining
This is one of the latest methods which is
catching up because of the growing ability to capture useful data accurately.
It involves the extraction of data from different kinds of multimedia sources
such as audio, text, hypertext, video, images, etc. and the data is converted
into a numerical representation in different formats. This method can be used
in clustering and classifications, performing similarity checks, and also to
identify associations.
2.
Ubiquitous Data Mining
This method involves the mining of data
from mobile devices to get information about individuals. In spite of having
several challenges in this type such as complexity, privacy, cost, etc. this
method has a lot of opportunities to be enormous in various industries
especially in studying human-computer interactions.
3.
Distributed Data Mining
This type of data mining is gaining
popularity as it involves the mining of huge amount of information stored in
different company locations or at different organizations. Highly sophisticated
algorithms are used to extract data from different locations and provide proper
insights and reports based upon them.
4.
Spatial and Geographic Data Mining
This is new trending type of data mining
which includes extracting information from environmental, astronomical, and
geographical data which also includes images taken from outer space. This type
of data mining can reveal various aspects such as distance and topology which
is mainly used in geographic information systems and other navigation
applications.
5.
Time Series and Sequence Data Mining
The primary application of this type of
data mining is study of cyclical and seasonal trends. This practice is also
helpful in analyzing even random events which occur outside the normal series
of events. This method is mainly being use by retail companies to access customer's buying patterns and their behaviors.
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