Deriving Queries From Examples Using Genetic Programming

Tae-Wan Ryu and Christoph F. Eick Department of Computer Science University of Houston Houston, Texas 77204-3475 {twryu,ceick}@cs.uh.edu

This paper centers on the problem of extracting intensional information for a set of objects from an object-oriented database. In our approach, the extracted intensional information for the given set of objects are described by object- oriented queries that compute this set of objects. The paper discusses the architecture of a knowledge discovery system, called MASSON, which employs genetic programming to find such queries, moreover, we will show how interesting queries that describe commonalities within a set of objects are automatically generated, modified, evaluated, and selected; we will also discuss how the search for the "best" query is conducted by the MASSON system. We also report on an experiment that evaluated the knowledge discovery capability of MASSON.