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KDD VS Data Mining

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johnnery esto

on 14 September 2012

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Transcript of KDD VS Data Mining

Data Mining -Knowledge discovery in databases
-Synonymous with large databases
-Automated discovery of patterns
and relationships What Is KDD? Why KDD? • Large databases are not uncommon
– Point of sale info, government records,
medical records, and credit card data
– Scientific instruments can produce
terabytes and petabytes at rates of gigs per
– Storage capabilities better. Cheaper, larger -Selection
-Reduction Coding
-Data Mining
-Visualization KDD Process Data mining algorithms find patterns in large
amounts of data by fitting models that are not
necessarily statistical models. What Is Data Mining? -Knowledge extraction
-Knowledge mining from databases
-Information discovery
-Information harvesting
-Exploratory data analysis
-Data archeology
-Data dredging
-Data pattern analysis
-Intelligent Data Analysis Other Terminology for Data
Mining In the Literature Data Mining Tasks * Predictive * Descriptive – find some human interpretable rules, relationships,
and/or patterns – Infers from current data to make predictions
– decision trees, neural networks, inductive logic
programming (ILP), regression algorithms -KDD is the process of finding patterns in
large databases
-Data Mining is one step in the process
-Open areas of research exist in other
steps of the process
-There are a wide breadth of successful
applications with more to come Conclusions Although, the two terms KDD and Data Mining are heavily used interchangeably, they refer to two related yet slightly different concepts. KDD is the overall process of extracting knowledge from data while Data Mining is a step inside the KDD process, which deals with identifying patterns in data. In other words, Data Mining is only the application of a specific algorithm based on the overall goal of the KDD process Difference between KDD and Data mining?
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