利用可比性映射改进双语数据分类：三模式数据分析视角
Exploiting a comparability mapping to improve bi-lingual data categorization: a three-mode data analysis perspective
摘要：
在本文中，我们解决的共同聚类和共同分类的双语数据奠定在两个语言相似性空间的可比性度量定义这两个空间之间的映射是可用的。提出了一种新的方法，我们可以表征为一个三模式的分析方案，提出了混合的可比性措施与两个相似性措施。我们的目标是共同提高在两个语言空间中执行的分类和聚类任务的准确性，以及可以获得的可比聚类的最终对齐的质量。我们首先使用一些纯合成的随机数据集来评估我们正式的相似性-可比性混合模型。然后，我们提出了两种变体的可比性措施，已定义（李和Gaussier 2010年）在双语词典提取的背景下，以适应聚类或分类任务。这两个变量的措施，随后用于评估我们的相似性，可比性混合模型的背景下，从维基百科的英语和法语类别收集的可比文本数据集的共同分类和共同聚类。我们的实验表明，在聚类和分类精度的明显改善时，混合相似性措施，与预期一样，更高的鲁棒性时，我们提出的两个可比性的变体措施，使用。我们认为，这种方法特别适合于建设质量可控的主题可比语料库。
英文摘要：
We address in this paper the co-clustering and co-classification of bilingual data laying in two linguistic similarity spaces when a comparability measure defining a mapping between these two spaces is available. A new approach that we can characterized as a three-mode analysis scheme, is proposed to mix the comparability measure with the two similarity measures. Our aim is to improve jointly the accuracy of classification and clustering tasks performed in each of the two linguistic spaces, as well as the quality of the final alignment of comparable clusters that can be obtained. We used first some purely synthetic random data sets to assess our formal similarity-comparability mixing model. We then propose two variants of the comparability measure that has been defined by (Li and Gaussier 2010) in the context of bilingual lexicon extraction to adapt it to clustering or categorizing tasks. These two variant measures are subsequently used to evaluate our similarity-comparability mixing model in the context of the co-classification and co-clustering of comparable textual data sets collected from Wikipedia categories for the English and French languages. Our experiments show clear improvements in clustering and classification accuracies when mixing comparability with similarity measures, with, as expected, a higher robustness obtained when the two comparability variant measures that we propose are used. We believe that this approach is particularly well suited for the construction of thematic comparable corpora of controllable quality.
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