• Corpus ID: 16246889

Discovery in Deductive Databases with Large eduction Results : The First Ste

  title={Discovery in Deductive Databases with Large eduction Results : The First Ste},
  author={Toru Yamada and Keiko Yamada and Yamada and Keiko},
Deducbve databases have the ability to deduce new facts from a set of facts using a set of rules. They are also useful in the integration of artificial intelligence and database. However, when recursive rules are involved, the amount of deduced facts can become too large to be practically stored, viewed or analyzed. This seriously hinders the usefulness of deductive databases. In order to overcome this problem, we propose four methods to discover characterisbc rules from large amount of… 

A review paper on deducting database in membrane computing

This paper is proposing the deduction of the complex database of the models created on the framework of membrane computing for designing framework in various models proposed by researches using membrane computing.



Knowledge Discovery in Databases: An Attribute-Oriented Approach

An attribute-oriented induction method has been developed for knowledge discovery in databases that integrates a machine learning paradigm with set-oriented database operations and extracts generalized data from actual data in databases.

An amateur's introduction to recursive query processing strategies

This paper surveys and compares various strategies for processing logic queries in relational databases and presents a set of sample rules and queries used for the performance comparisons and gives an analytical solution for each query/rule system.

Fast Algorithms for Mining Association Rules

Two new algorithms for solving thii problem that are fundamentally different from the known algorithms are presented and empirical evaluation shows that these algorithms outperform theknown algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems.

Frawley, eds., AAAI Press/The MIT Press, pp 449-462,1991 W Klosgen, “Visualization and Adaptivity in the Statistics Interpreter EXPLORA,

  • Proc AAAl ’91 Workshop Knowledge Discovery zn Databases,
  • 1991