SIFT: An Algorithm for Extracting Structural Information From Taxonomies
This addresses taxonomy alignment for domains where textual information is insufficient, though it appears incremental as it builds on existing structural analysis techniques.
The authors tackled the problem of extracting structural information from taxonomies to enable merging, presenting SIFT, a 3-step algorithm that leverages hierarchical structures to infer correspondences, particularly useful when text-based alignment methods fail.
In this work we present SIFT, a 3-step algorithm for the analysis of the structural information represented by means of a taxonomy. The major advantage of this algorithm is the capability to leverage the information inherent to the hierarchical structures of taxonomies to infer correspondences which can allow to merge them in a later step. This method is particular relevant in scenarios where taxonomy alignment techniques exploiting textual information from taxonomy nodes cannot operate successfully.