Abstract
An algorithm based on facet classification is proposed to reorder suggestions of resource annotations. It finds the most common pattern of facets used over data in order to reorder according to the suggested annotation class and its popularity. The algorithm is applied to a real, large dataset of a well-known online repository, showing an improvement of 63% in terms of precision on the selected annotations according to the order that they were presented. The objective is to provide a higher assertion number between suggested annotations and those chosen by the user to annotate a resource.
