Using domain knowledge to optimize the knowledge discovery process in databases

Abstract

Modern database technologies process large volumes of data to discover new knowledge. Some large databases make discovery computationally expensive. Additional knowledge, known as domain or background knowledge, can often guide and restrict the search for interesting knowledge. This paper discusses mechanisms by which domain knowledge can be used effectively in discovering knowledge from databases. In particular, we look at the use of domain knowledge to reduce the size of the database for discovery, to optimize the hypotheses which represent the interesting knowledge to be discovered, to optimize the queries used to prove the hypotheses, and to avoid possible redundant and contradictory rule discovery. Some experimental results using the IDIS knowledge discovery tool is provided. ©2000 John Wiley & Sons, Inc.