This will allow the public a better perception of the pattern and will decrease the controversy. Summary The workshop confirmed that knowledge discovery in databases is an idea whose time has come. It should be used to reduce search space, but used carefully so as not to prevent un-anticipated discoveries. While a specialized learning algorithm will outperform a general method, a desirable compromise is to develop a framework for augmenting the general method with the specific domain knowledge. Dealing with Uncertainty .
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.