  Natural language processing is an important discipline with the aim of
understanding text by its digital representation, that due to the diverse way
we write and speak, is often not accurate enough. Our paper explores different
graph-related algorithms that can be used in solving the text summarization
problem using an extractive approach. We consider two metrics: sentence overlap
and edit distance for measuring sentence similarity.
