Automatic Recommendations for Machine-Assisted Multimedia Annotation: a Knowledge-Mining Approach

Abstract. Recommender systems apply knowledge discovery techniques to help in nding associated information. In this paper, we investigate the use of association rule mining as an underlying technology for a recommender system aimed at improving the annotation process of mul-timedia news documents. The accuracy of these systems is very sensitive to the number of already annotated news items (the "cold-start " prob-lem); ontology-based semantic relations are being used to alleviate this situation.