We investigated several algorithms for automatically mapping one topical taxonomy onto another, assuming that each taxonomy is populated with documents. We also devised an experimental method of evaluating taxonomy mapping algorithms. This paper describes the taxonomy mapping algorithms, the experiments to evaluate them, and the results of the experiments. We conclude that a Centroid-like algorithm produces the best results when mapping one taxonomy onto a very similar taxonomy, but that a kNN-like algorithm performs better when mapping one taxonomy onto a dissimilar taxonomy.
By: Guy T. Hochgesang, Bhavani Iyer, Bernard S. Landman, Zvi P. Weiss
Published in: RC22315 in 2001
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