  Multi-Sentence Compression (MSC) aims to generate a short sentence with the
key information from a cluster of similar sentences. MSC enables summarization
and question-answering systems to generate outputs combining fully formed
sentences from one or several documents. This paper describes an Integer Linear
Programming method for MSC using a vertex-labeled graph to select different
keywords, with the goal of generating more informative sentences while
maintaining their grammaticality. Our system is of good quality and outperforms
the state of the art for evaluations led on news datasets in three languages:
French, Portuguese and Spanish. We led both automatic and manual evaluations to
determine the informativeness and the grammaticality of compressions for each
dataset. In additional tests, which take advantage of the fact that the length
of compressions can be modulated, we still improve ROUGE scores with shorter
output sentences.
