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Semantic matching


  uses contextual attributes of the digital object to interpret the artifact in a manner that more closely corresponds with human perceptual categories. For example, perceptual hashes allow the matching of visually similar images and are unconcerned with the low-level details of how the images are persistently stored. Semantic methods tend to provide the most specific results but also tend to be the most computationally expensive ones.
NIST SP 800-168