Enabling Advanced Context-Based Multimedia Interpretation Using Linked Data

Current search technologies can only harness the ever increasing amount of multimedia data when sufficient metadata exists. Several annotations are already available, yet they seldom cover all aspects. The generation of additional metadata proves costly; therefore efficient multimedia retrieval requires automated annotation methods. Current feature extraction algorithms are limited because they do not take context into account. In this article, we indicate how Linked Data can provide information that is vital to create an interpretation context. As a result, advanced interactions between algorithms, information and context will enable more advanced interpretation of multimedia data. Eventually, this will reflect in better search possibilities for the end user.