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IEEE 2016 PROJECTS DOTNET

 
 
Data Mining:
DEFINITION
»
Data Mining is the computational process of discovering patterns in the large data sets involving Artificial Intelligence, Machine Learning, Statistics and Database Systems. It’s main aim being “to extract information from a data set and transform it into a understandable structure for further usage”.
 
INTRODUCTION
»
In general data mining is the process of analyzing data from different perspectives and summarizing it into useful information.
 
»
It generally results in the discovery of new patterns in large data sets.
 
»
It facilitates users to analyze data from different dimensions/perspectives, categorize it and summarise the relationships.
 
» It can also be stated as sorting through data to identify patterns and establish relationships.
 
» Companies use this technique to transform raw data into useful information.
 
» It makes use of techniques such as Artificial Intelligence, Neural networks, and advanced statistical tools to reveal trends, pattern and relationships.
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Block Diagram
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Data mining process for health care systems
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Features:
 

Marketing / Retail

  • Data mining helps marketing companies to build models for historical data.

Finance / Banking

  • It powers information for the financial institutions about loan and credit reporting.

Manufacturing

  • Applying data mining in operational engineering helps manufacturers to find faulty equipments.

Governments

  • Facilitates government agencies to track and analyze the records.

Marketing Strategies (Campaigns)

  • Data mining is used here for the purpose of solid customer focus.

Economic Processing

  • Data mining is generally used for resourceful means of data collections across the world.
   
Real Time Examples:
 

Data mining is being used in day-to-day activities both directly and indirectly. Some of them are

  • Super Markets
  • Marketing Firms
  • Search engines
  • Customer Research Labs
   
 
 
 
 
 
 
   
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