  Topic detection becomes more important due to the increase of information
electronically available and the necessity to process and filter it. In this
context our master's thesis work was carried out, where we proposed to present
a new approach to the detection of topics called ClusART. Thus, we proposed a
three-phase approach, namely : a first phase during which lexical preprocessing
was conducted. A second phase during which the construction and generation of
vectors representing the documents was carried out. A third phase which is
itself composed of two steps. In the first step we used the FuzzyART algorithm
for the training phase. In the second step we used a classifier using Paragraph
Vector for the test phase. The comparative study of our approach on the 20
Newsgroups dataset showed that our approach is able to detect almost relevant
topics.
