, Volume 42, Issue 3, pp 319–345 | Cite as

Additive similarity trees

  • Shmuel Sattath
  • Amos Tversky


Similarity data can be represented by additive trees. In this model, objects are represented by the external nodes of a tree, and the dissimilarity between objects is the length of the path joining them. The additive tree is less restrictive than the ultrametric tree, commonly known as the hierarchical clustering scheme. The two representations are characterized and compared. A computer program, ADDTREE, for the construction of additive trees is described and applied to several sets of data. A comparison of these results to the results of multidimensional scaling illustrates some empirical and theoretical advantages of tree representations over spatial representations of proximity data.

Key words

proximity clustering multidimensional scaling 


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Copyright information

© Psychometric Society 1977

Authors and Affiliations

  • Shmuel Sattath
    • 1
  • Amos Tversky
    • 1
  1. 1.Dept. of PsychologyThe Hebrew UniversityJerusalemIsrael

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