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In this paper, we overview the semantic gap problem in multimedia and discuss how machine learning and symbolic AI can be combined to narrow this gap. We describe the semantic gap in terms of a classical architecture for multimedia processing and discuss a structured approach to bridge it. Such an approach combines machine learning (for mapping signals to objects) and symbolic AI (for linking objects to meaning). Our main goal is to raise awareness and discuss the challenges involved in such a structured approach to multimedia understanding, especially in the view of the latest developments in machine learning and symbolic AI.
Nahal Mansouri, Sahand Jamal Rahi, Soroush Setareh
Sébastien Louis Alexandre Rouault