首页> 外文会议>Mexican International Conference on Artificial Intelligence(MICAI 2007); 20071104-10; Aguascalientes(MX) >A New Hybrid Summarizer Based on Vector Space Model, Statistical Physics and Linguistics
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A New Hybrid Summarizer Based on Vector Space Model, Statistical Physics and Linguistics

机译:基于向量空间模型,统计物理和语言学的新型混合摘要器

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In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.
机译:在本文中,我们提出了一种自动汇总西班牙医学文本的混合方法。有很多使用统计或语言学进行自动汇总的系统,但是只有少数几个系统结合了这两种技术。我们的想法是,要获得良好的总结,我们需要使用文本的语言方面,但同时我们也应受益于统计技术的优势。我们已经将Cortex(向量空间模型)和Enertex(统计物理学)系统与Yate术语提取器和Disicosum系统(语言学)结合在一起。我们已经比较了这些系统,然后将它们集成为一种混合方法。最后,我们将此混合系统应用于大量医疗文章,并评估了它们的性能并获得了良好的效果。

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