A Combination between Textual and Visual Modalities for Knowledge Extraction of Movie Documents

Manel Fourati, Anis Jedidi, Faiez Gargouri


In view of the proliferation of audiovisual documents and the indexing limits mentioned in the literature, the progress of a new solution requires a better description extracted from the content. In this paper, we propose an approach to improve the description of the cinematic audiovisual documents. However, this consists not only in extracting the knowledge meaning conveyed in the content but also combining textual and visual modalities. In fact, the semiotic desription represents important information from the content. We propose in this paper an approach based on the use of pre and post production film documents. Consequently, we concentrate efforts to extract some descriptions about the use not only of the probalistic Latent Dirichlet Allocation (LDA) model but also of the semantic ontology LSCOM. Finally, a process of identifying a description is highlighted. In fact, the experimental results confirmed the importance of the performance of our approach through the comparison of our result with a human jugment and a semi-automatic method by using the MovieLens dataset.


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