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Data-Mining

COMP207 Lectures

This is a more general form of OLAP. They refer to the discovery of patterns or knowledge in data

Applications of Data-Mining

  • Deviation Detection - Identifying anomalies such as intruders.
  • Link Analysis - Trying the discover links between attributes.
    • These can be used to make association rules.
  • Predictive Modelling - Trying to predict future behaviour of certain attributes in the data base on pas behaviour.
  • Database Segmentation - Grouping data by similar behaviour.
    • Group customers based on spending habits.
    • Group customers based on reaction of a marketing campaign.

Types of Discovered Knowledge

  • Association Rules:
    • People who buy nappies buy beer.
  • Classification Hierarchies:
    • Classification of mutual funds based on performance data characteristics such as growth, income and stability.
  • Sequential Patterns:
    • If a patient underwent cardiac bypass surgery for blocked arteries and an aneurysm and later developed high blood urea within a year of surgery, they is likely to suffer from kidney failure within the next 18 months.
  • Clustering:
    • Group treatment data on a disease based on similarity of side effects.