Databases typically have missing, incomplete or incorrect data items. Thus any discovery algorithm must deal with noise. Rules discovered in noisy data will necessarily be approximate. Exponential and even high-order polynomial algorithms will not scale for dealing with large volumes of data. Incremental Approaches .
Incremental algorithms are desirable for dealing with with changing data.
Interactive Systems . Such tools would go far beyond the existing statistical tools and significantly enhance the human capabilities for data analysis. The incremental, interactive discovery methods may transform the static databases of today into evolving information systems of tomorrow. Caution is required for discovery on demographic databases, to avoid findings that are illegal or unethical. Deductive and object-oriented database systems can provide some of the needed support for induction on large volumes of data.