Abstract. We propose a method of synonymous paraphrasing of a text based on WordNet synonymy data and Internet statistics of stable word combinations (collocations). Given a text, we look for words or expressions in it for which WordNet provides synonyms, and substitute them with such synonyms only if the latter form valid collocations with the surrounding words according to the statistics gathered from Internet. We present two important applications of such synonymous paraphrasing: (1) style-checking and correction: automatic evaluation and computer-aided improvement of writing style with regard to various aspects (increasing vs. decreasing synonymous variation, conformistic vs. individualistic selection of synonyms, etc.) and (2) steganography: hiding of additional information in the text by special selection of synonyms. A basic interactive algorithm of style improvement is outlined and an example of its application to editing of newswire text fragment in English is traced. Algorithms of style evaluation and information hiding are also proposed.

Abstract.A method is proposed of the automatic concealment of digital information in rather long orthographically and semantically correct texts. The method does not change the meaning of the source text; it only replaces some words by their synonyms. Groups of absolute synonyms are used in a context independent manner, while the groups of relative synonyms are previously tested for semantic compatibility with the collocations containing the word to be replaced. A specific replacement is determined by the hidden information. The collocations are syntactically connected and semantically compatible pairs of content words; they are massively gathered beforehand, with a wide diversity in their stability and idiomacity. Thus the necessary linguistic resources are a specific synonymy dictionary and a very large database of collocations. The steganographic algorithm is informally outlined. An example of hiding binary information in a Russian text fragment is manually traced, with a rough evaluation of the steganographic bandwidth.

Abstract. The problem of automatic text segmentation is subcategorized into two different problems: thematic segmentation into rather large topically selfcontained sections and splitting into paragraphs, i.e., lexico-grammatical segmentation of lower level. In this paper we consider the latter problem. We propose a method of reasonably splitting text into paragraph based on a text cohesion measure. Specifically, we propose a method of quantitative evaluation of text cohesion based on a large linguistic resource -a collocation network. At each step, our algorithm compares word occurrences in a text against a large DB of collocations and semantic links between words in the given natural language. The procedure consists in evaluation of the cohesion function, its smoothing, normalization, and comparing with a specially constructed threshold.