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Knowledge Discovery in Databases: An Information Retrieval Perspective




The current trend of increasing capabilities in data generation and collection has resulted in an urgent need for data mining applications, also called knowledge discovery in databases. This paper identifies and examines the issues involved in extracting useful grains of knowledge from large amounts of data. It describes a framework to categorise data mining systems. The author also gives an overview of the issues pertaining to data pre processing, as well as various information gathering methodologies and techniques. The paper covers some popular tools such as classification, clustering, and generalisation. A summary of statistical and machine learning techniques used currently is also provided.

Author(s): Ong, CS.
Journal: Malaysian Journal of Computer Science
Volume: 13
Number (issue): 2
Pages: 54-63
Year: 2000
Month: December
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF


  title = {Knowledge Discovery in Databases: An Information Retrieval Perspective},
  author = {Ong, CS.},
  journal = {Malaysian Journal of Computer Science},
  volume = {13},
  number = {2},
  pages = {54-63},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = dec,
  year = {2000},
  month_numeric = {12}