@inproceedings{SisLab3045,
       booktitle = {The International Conference on Pattern Recognition and Artificial Intelligence},
           month = {July},
           title = {AniAge Ontology for Movement Classification in Vietnamese Dance},
          author = {Telli Abdelmoutia and Thi Chau Ma and Bourahla Mustapha and Tabia Karim and Benferhat Salem},
            year = {2018},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3045/},
        abstract = {This paper proposes an OWL ontology called {$\backslash$}AniAge", to
define taxonomy of dance movement classes and their relationships for the traditional Vietnamese dance taking into account the semantics of its art and its cultural anthropologists. The {$\backslash$}AniAge" terminology can be used to describe elementary movements (poses) as a dataset ontology importing {$\backslash$}AniAge". These poses are results of dance sequences segmentation (using segmentation techniques). The ontolgy {$\backslash$}AniAge" is supported by classification rules, which are developed with the OWL complementary language SWRL (Semantic Web Rule Language) to entail movement phrases,
which are basic movements with complete meaning. The
dataset ontology containing poses descriptions can be queried using the query language SQWRL (Semantic Query Webenhanced Rule Language), which is extension of SWRL to
retrieve implicit dance knowledge. Then, the query answers
can be used for computer animation.}
}