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Titlebook: Computational Linguistics and Intelligent Text Processing; 9th International Co Alexander Gelbukh Conference proceedings 2008 Springer-Verl

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Kontinuumsmechanische Grundlagen,tic information about both arguments and adjuncts of verbs. When combined with our best performing classifier (a novel Gaussian classifier), it yields the promising accuracy of 64.2% in classifying 204 verbs to 17 Levin (1993) classes. We discuss the impact of our results on the state-or-art and propose avenues for future work.
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https://doi.org/10.1007/3-540-32487-9rd similarity. This work presents a linear time complexity approximative algorithm for computing word similarity without any dimensionality reduction. It then introduces a large-scale evaluation based on two languages and two knowledge sources and discusses the underlying reasons for the relative performance of each measure.
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Acquisition of Elementary Synonym Relations from Biological Structured Terminologysing the terminological resource .. It provides results with over 93% precision. Comparison with an existing synonym resource (the general-language resource .) shows that there is a very small overlap between the induced lexicon of synonyms and the . synsets.
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A Comparison of Co-occurrence and Similarity Measures as Simulations of Contextrd similarity. This work presents a linear time complexity approximative algorithm for computing word similarity without any dimensionality reduction. It then introduces a large-scale evaluation based on two languages and two knowledge sources and discusses the underlying reasons for the relative performance of each measure.
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