  The size of 3D models used on the web or stored in databases is becoming
increasingly high. Then, an efficient method that allows users to find similar
3D objects for a given 3D model query has become necessary. Keywords and the
geometry of a 3D model cannot meet the needs of users' retrieval because they
do not include the semantic information. In this paper, a new method has been
proposed to 3D models retrieval using semantic concepts combined with shape
indexes. To obtain these concepts, we use the machine learning methods to label
3D models by k-means algorithm in measures and shape indexes space. Moreover,
semantic concepts have been organized and represented by ontology language OWL
and spatial relationships are used to disambiguate among models of similar
appearance. The SPARQL query language has been used to question the information
displayed in this language and to compute the similarity between two 3D models.
We interpret our results using the Princeton Shape Benchmark Database and the
results show the performance of the proposed new approach to retrieval 3D
models. Keywords: 3D Model, 3D retrieval, measures, shape indexes, semantic,
ontology
