Development and application of a metric on semantic nets

Motivated by the properties of spreading activation and conceptual distance, the authors propose a metric, called Distance, on the power set of nodes in a semantic net. Distance is the average minimum path length over all painvise combinations of nodes between two subsets of nodes. Distance can be successfully used to assess the conceptual distance between sets of concepts when used on a semantic net of hierarchical relations. When other kinds of relationships, like “cause,” are used, Distance must be amended but then can again be effective. The judgments of Distance significantly correlate with the distance judgments that people make and help us determine whether semantic net SI is better or worse than semantic net S,. First a “conceptual distance” task is set, and people are asked to perform it. Then the same task is performed by Distance on SI and &. If Distance on SI performs more like people than Distance on S,, the conclusion is that SI is better than S,. Distance embedded in the methodology facilitates repeatable quantitative experiments.