Multi-document Summarization Based on Locally Relevant Sentences

Multi-document summarization systems must be able to draw the "best" information from a set of documents.In this paper we propose a novel extractive approach for multidocument summarization based on the detection of locally relevant sentences. Our main hypothesis is that by extracting relevant sentences from each document within a collection, instead of considering all documents at once, the final multi-document summary will be of higher quality. Performed experiments showed that the proposed method is able to outperform conventional baselines as well as traditional approaches by constructing summaries of high quality according to the ROUGE evaluation metrics.