A method for extracting terms from technical texts based on a new terminology measure is described. Morphological constraints are used to select term candidates. The results of experiments based on a corpus of texts in the area of computer aided design systems and computer graphics are described.

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In this paper, we construct paraphrase graphs for news text collections (clusters). Our aims are, first, to prove that paraphrase graph construction method can be used for news clusters identification and, second, to analyze and compare stylistically different news collections. Our news collections include dynamic, static and combined (dynamic and static) texts. Their respective paraphrase graphs reflect their main characteristics. We also automatically extract the most informationally important linked fragments of news texts, and these fragments characterize news texts as either informative, conveying some information, or publicistic ones, trying to affect the readers emotionally.

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