  In this paper, we propose a system for contextual and semantic Arabic
documents classification by improving the standard fuzzy model. Indeed,
promoting neighborhood semantic terms that seems absent in this model by using
a radial basis modeling. In order to identify the relevant documents to the
query. This approach calculates the similarity between related terms by
determining the relevance of each relative to documents (NEAR operator), based
on a kernel function. The use of sliding window improves the process of
classification. The results obtained on a arabic dataset of press show very
good performance compared with the literature.
