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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,...
In a Web of increasing size and complexity, a key issue is automatic document organization, which includes topic extraction in collections. Since we consider topics as document clusters with semantic properties, we are concerned with exploring suitable clustering techniques for their identification on hyperlinked environments (where we only regard structural information). For this purpose, three algorithms...
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