Name
Abstract | ||
|---|---|---|
With the rapid but still incomplete maturation of the information retrieval research related to multimedia document, the progress of a new solution requires the extraction of semantic information from the content. It should be however, not only extracted from the content but it should also present the different semiotics meaning conveyed in the content. In our work, we concentrate our efforts on the movie documents. In fact, the knowledge extracted separately can conceal the global vision on the sequence of events or analysis of history conveyed in a film. In this context, we are interested in this paper to generate relationships either between sub-parts of the same movie or between movies. Consequently, we propose an inference reasoning to build these relationships in order to reveal the hidden knowledge semantics of resources. These relationships are basically based on the semiotic description that poses a major challenge. A case study where we substantiate and prove the accurate performance of our proposed process is highlighted. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-47650-6_19 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
Semiotic,Movie,Rule,Inference | Information retrieval,Semiotics,Computer science,Inference,Semantic information,Artificial intelligence,Multimedia document,Machine learning,Semantics | Conference |
Volume | ISSN | Citations |
9983 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manel Fourati | 1 | 10 | 2.66 |
| Anis Jedidi | 2 | 28 | 11.90 |
| Faïez Gargouri | 3 | 244 | 92.29 |