Juan-Manuel Torres-Moreno

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We study correlation of rankings of text summarization systems using evaluation methods with and without human models. We apply our comparison framework to various well-established contentbased evaluation measures in text summarization such as coverage, Responsiveness, Pyramids and ROUGE studying their associations in various text summarization tasks(More)
We present SMMR, a scalable sentence scoring method for query-oriented update summarization. Sentences are scored thanks to a criterion combining query relevance and dissimilarity with already read documents (history). As the amount of data in history increases, non-redundancy is prioritized over query-relevance. We show that SMMR achieves promising results(More)
In this article we present the RST Spanish Treebank, the first corpus annotated with rhetorical relations for this language. We describe the characteristics of the corpus, the annotation criteria, the annotation procedure, the inter-annotator agreement, and other related aspects. Moreover, we show the interface that we have developed to carry out searches(More)
This paper presents two corpora produced within the RPM2 project: a multi-document summarization corpus and a sentence compression corpus. Both corpora are in French. The first one is the only one we know in this language. It contains 20 topics with 20 documents each. A first set of 10 documents per topic is summarized and then the second set is used to(More)
In this paper, we present the participation of the Computer Science Laboratory of Avignon (LIA) to RepLab 2013 edition. RepLab is an evaluation campaign for Online Reputation Management Systems. LIA has produced a important number of experiments for every tasks of the campaign: filtering, topic priority detection, Polarity for Reputation and topic(More)
Since information in electronic form is already a standard, and that the variety and the quantity of information become increasingly large, the methods of summarizing or automatic condensation of texts is a critical phase of the analysis of texts. This article describes Cortex a system based on numerical methods, which allows obtaining a condensation of a(More)
Hopfield [1, 2] took as a starting point physical systems like the magnetic Ising model �formalism resulting from statistical physics describing a system composed of units with two possible states named spins) to build a Neural Network �NN) with abilities of learning and recovery of patterns. The capacities and limitations of this Network, called(More)
This paper discusses an approach to topic-oriented multidocument summarization. It investigates the effectiveness of using additional information about the document set as a whole, as well as individual documents. We present NEO-CORTEX, a multi-document summarization system based on the existing CORTEX system. Results are reported for experiments with a(More)