Knowledge Discovery from Databases (KDD) Research Task

A Knowledge Discovery from Databases (KDD) Research Task is a research task that studies a KDD research question (within a data mining research area).

• Context:
  • It can propose new Data Mining Tasks.
  • It can study ways to improve Data Mining Algorithms.
  • It can involve a Data Mining Research Project.
  • It can involve the publication of results in a Data Mining Research Conference or Data Mining Research Journal.
  • It can analyze Data Mining Systems.
  • It can range from being a Applied Data Mining Research to Basic Data Mining Research.
  • It can be instantiated as a Data Mining Research Act.
  • It can result in an Data Mining Research Paper.
  • …
• Counter-Example(s):
  • a Statistics Research Task.
• See: AI Research, Machine Learning Research, Statistical Inference Research.

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References

1995

• (Han et al., 1995) ⇒ Jiawei Han, Yongjian Fu, Krzysztof Koperski, Gabor Melli, Wei Wang, and Osmar R. Zaiane. (1995). “Knowledge Mining in Databases: An Integration of Machine Learning Methodologies with Database Technologies." Canadian AI Magazine, 38.
  • QUOTE: Active research has been conducted on knowledge discovery in databases by the researchers in our group for years, with many interesting results published and a prototyped knowledge discovery system, DBMiner (previously called DBLearn), developed and demonstrated in several conferences.

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