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.
Taxonomy alignment techniques are able to detect taxonomy concepts that are equivalent. But, when can we say that two concepts are equivalent? If we attend only to the text label for representing the concepts, we can find many examples in everyday life, for instance, and or and seem to be equivalent concepts since they represent the same real idea or object. However, it is well known that when taxonomies are used as knowledge sources, the way users perceive the degree of likeness between pairs of concepts is highly dependent on the domain being explored @cite_2 . Therefore, synonymy between text labels is not always an equivalence indicator, so it is necessary to focus in the context the concepts are being considered.
@cite_2
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A valve unit for a flowing medium is combined with an electrical measuring system to provide measurement of the rate of flow of the medium. The valve unit is connected to a propeller-type rotor disposed in a conduit which communicates with the valve. The rotor incorporates a permanent magnet in at least one vane thereof and the measuring system includes a magnetic pulse generator which senses the magnetic field produced by the magnet and generates a corresponding train of pulses during the rotation of the rotor. An amplifier-differentiator connected to the pulse generator produces an output in accordance with the derivative of the pulses so as to provide an indication of the rate of flow.