Authors:
Manel Fourati
;
Anis Jedidi
and
Faiez Gargouri
Affiliation:
MIR@CL Laboratory, University of Sfax, Sfax and Tunisia
Keyword(s):
Description, Segmentation, Movie Document, Textual, Visual Modalities, Knowledge, LDA.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Communication and Software Technologies and Architectures
;
e-Business
;
Enterprise Information Systems
;
Knowledge Acquisition
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
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 o
ur result with a human jugment and a semi-automatic method by using the MovieLens dataset.
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