Resumen

LITVAK, Marina  y  VANETIK, Natalia. Multi-document Summarization using Tensor Decomposition. Comp. y Sist. [online]. 2014, vol.18, n.3, pp.581-589. ISSN 2007-9737.  https://doi.org/10.13053/CyS-18-3-2026.

The problem of extractive text summarization for a collection of documents is defined as selecting a small subset of sentences so the contents and meaning of the original document set are preserved in the best possible way. In this paper we present a new model for the problem of extractive summarization, where we strive to obtain a summary that preserves the information coverage as much as possible, when compared to the original document set. We construct a new tensor-based representation that describes the given document set in terms of its topics. We then rank topics via Tensor Decomposition, and compile a summary from the sentences of the highest ranked topics.

Palabras llave : Tensor decomposition; multilingual multi-focument summarization.

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