- 1 - SEMANTIC DISTANCE IN CONCEPTUAL GRAPHS Norman Foo 1 , Brian J. Garner 2 , Anand Rao 3 and Eric Tsui 4 Abstract A modification of Sowa’s metric on conceptual graphs is proposed and defended. The metric is computed by locating the least subtype which subsumes the two given types, and adding the distance from each given type to the subsuming type. Implementations using this metric are described, the relevance of it to fuzzy problems is explained. 1. Proposed Metric Given two concepts C1 and C2 with types T1 and T2, Garner and Tsui (1987) have proposed a modification of Sowa’s semantic distance between C1 and C2 as follows. Find the concept C3 which generalizes C1 and C2 with type T3 such that T3 is the most specific type which subsumes T1 and T2; the semantic distance between C1 and C2 is the sum of the distances from C1 to C3 and C2 to C3. It should be clear that this is indeed a metric, satisfying reflexivity, symmetry and the triangle inequality. In this paper we explain this definition in several ways, describe its use in an extensive implementation, and suggest how it may help solve problems in fuzzy concepts. 2. Implementation and Explanations Garner and Tsui (1987) first used this metric in an important component of the conceptual graph systems that were designed in Deakin University. They have applied this semantic distance to study a memory model that can — store graphs without predefining a fixed set of attributes (ie. labels); _ ______________ 1. Computer Science Dept., University of Sydney, Sydney, Australia 2006. e-mail: norman@cs.su.oz.au 2. Dept. of Computing and Mathematics, Deakin University, Geelong, Australia 3217. e-mail: brian@aragorn.oz.au 3. Australian Artificial Intelligence Institute, 1 Grattan St., Carlton, Australia 3053. e-mail: anand@yarra-glen.aaii.oz.au 4. Expert Systems Group, Continuum Australia, 100 Mount Street, North Sydney, Australia 2060. e-mail: eric@cs.su.oz.au