Automatic Summarization (AS) in Brazil has only recently become a significant research topic. When compared to other languages initiatives, such a delay can be explained by the lack of specific resources, such as expressive lexicons and corpora that could provide adequate foundations for deep or shallow approaches on AS. Taking advantage of having commonalities with respect to resources and a corpus of texts and summaries written in Brazilian Portuguese, two NLP research groups have decided to start a common task to assess and compare their AS systems. In the experiment five distinct extractive AS systems have been assessed. Some of them incorporate techniques that have been already used to summarize texts in English; others propose novel approaches to AS. Two baseline systems have also been considered. An overall performance comparison has been carried out, and its outcomes are discussed in this paper
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