  Summaries are important when it comes to process huge amounts of information.
Their most important benefit is saving time, which we do not have much
nowadays. Therefore, a summary must be short, representative and readable.
Generating summaries automatically can be beneficial for humans, since it can
save time and help selecting relevant documents. Automatic summarization and,
in particular, Automatic text summarization (ATS) is not a new research field;
It was known since the 50s. Since then, researchers have been active to find
the perfect summarization method. In this article, we will discuss different
works in automatic summarization, especially the recent ones. We will present
some problems and limits which prevent works to move forward. Most of these
challenges are much more related to the nature of processed languages. These
challenges are interesting for academics and developers, as a path to follow in
this field.
