Judging Similarity among Strings Described By Hierarchical Trees
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The paper compares the tree-theoretical model of similarity judgement (in which the similarity between two objects is a function of the distance between them in a conceptual tree) with an averaging model of similarity judgement that is drawn jointly from information integration theory and from current research indicating the prevalence of anchoring and adjustment mechanisms in judgement. Results of an experiment are presented that suggest that even when subjects organize conceptual material as a hierarchical tree, judgments of similarity among the objects are better accounted for by an averaging mechanism than by distances in the tree. These data are discussed in terms of the differences between the representation in which knowledge is encoded and the processes that operate on the represented information.