Review of Data mining (Knowledge discovery) in the Future

Surender Kumar, Kanwaldip Kaur

Abstract


Data mining (sometimes called data or knowledge
discovery) is the process of analyzing data from different
perspectives and summarizing it into useful information -
information that can be used to increase revenue, cuts costs, or
both. Data mining software is one of a number of analytical
tools for analyzing data. It allows users to analyze data from
many different dimensions or angles, categorize it, and
summarize the relationships identified. Technically, data mining
is the process of finding correlations or patterns among dozens
of fields in large relational databases.
The term data mining is often used to apply to the two separate
processes of knowledge discovery and prediction. Knowledge
discovery provides explicit information that has a readable form
and can be understood by a user (e.g., association rule mining).
Forecasting, or predictive modeling provides predictions of
future events and may be transparent and readable in some
approaches (e.g., rule-based systems) and opaque in others such
as neural networks. Moreover, some data-mining systems such
as neural networks are inherently geared towards prediction
and pattern recognition, rather than knowledge discovery. In
Future different Scope of data mining are.
1. Developing a unifying theory of data mining.
2. Scaling up for high dimensional data and high speed
data streams.
3. Data mining in a network setting.
4. Data mining for biological and environmental
problems.
5. Security, privacy and data integrity.
6. Dealing with non-static, unbalanced and cost-sensitive
data


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DOI: https://doi.org/10.26483/ijarcs.v7i6.2778

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