论文信息 - Knowledge Discovery in Databases and Data Mining

Knowledge Discovery in Databases and Data Mining

This paper gives an overview on some approaches of knowledge discovery in databases (KDD). First, the types of information exploited in a KDD process and the characteristics of this process are summarized. Then we descibe a classification of KDD-patterns. Types of languages to build subgroups of objects and the role of domain knowledge are discussed. Finally, the architecture of modular KDD systems is presented and topics of efficiency are treated.

Willi Klösgen | W. Klösgen

[1] Friedrich Gebhardt. Interessantheit als Kriterium für die Bewertung von Ergebnissen , 1994, Inform. Forsch. Entwickl..

[2] Arno Siebes,et al. Data Surveying: Foundations of an Inductive Query Language , 1995, KDD.

[3] Gregory Piatetsky-Shapiro,et al. Knowledge Discovery in Databases: An Overview , 1992, AI Mag..

[4] Katharina Morik,et al. Knowledge Acquisition and Machine Learning: Theory, Methods, and Applications , 1993 .

[5] Heikki Mannila,et al. Discovering Frequent Episodes in Sequences , 1995, KDD.

[6] Willi Klösgen,et al. Knowledge discovery in databases terminology , 1996, KDD 1996.

[7] Willi Klösgen,et al. Explora: A Multipattern and Multistrategy Discovery Assistant , 1996, Advances in Knowledge Discovery and Data Mining.