Goal-Driven Similarity Assessment

Dietmar Janetzko Dept. of Cognitive Science University of Freiburg W{7800 Freiburg Stefan Wess Dept. of Computer Science University of Kaiserslautern W{6750 Kaiserslautern Erica Melis Dept. of Computer Science University of Saarbr ucken W{6600 Saarbr ucken Abstract While most approaches to similarity assessment are oblivious of knowledge and goals, there is ample evidence that these elements of problem solving play an important role in similarity judgements. This paper is concerned with an approach for integrating assessment of similarity into a framework of problem solving that embodies central notions of problem solving like goals, knowledge and learning. We review empirical ndings that unravel characteristics of similarity assessment most of which have not been covered by purely syntactic models of similarity. A formal account of similarity assessment that allows for the integration of central ideas of problem solving is developed. Given a goal and a domain theory, an appropriate perspective is taken that brings into focus only goal-relevant features of a problem description as input to similarity assessment.