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

Recommender systems apply knowledge discovery techniques to help in finding 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 multimedia news documents. The accuracy of these systems is very sensitive to the number of already annotated news items (the ”cold-start” problem); ontology-based semantic relations are being used to alleviate this situation.

• Type: Conference
• Year: 2007
• Where: SAMT
• Authors: Mónica Díez, Paulo Villegas
• Keywords: Association Rule Mining, Recommender System, SAMT 2007, Systems Apply Knowledge