The paper provides an overview of systems for scientometric analysis and considers methods for identifying current research directions. The new method for research directions detection based on full-text clustering is proposed. The results of experiments on the detection of the directions of the field "regenerative medicine" are presented. The prospects of method, its drawbacks and directions for further research are discussed.

The paper analyses linguo-cultural characteristics of business negotiations such as discourse lexis, emotional colouring level, metaphor phrases, professional jargon and other linguistic and speech means from the perspective of computational linguistics. Different specific features of the language of business and professional communication are represented in terms of automatic text analysis methods. The possible ways of extraction of these features from texts are considered. The formal model of the language based on cognitive structures has been developed. The model is oriented for business negotiations and scientific texts. It can be used as a helpful means for communicants who speak imperfect English for determination of the extent to which their texts relate to business and professional communication. The model can also be used in distance learning systems for detection of errors in text writing. The authors draw the conclusion about prospects for practical application of the proposed model and discuss directions for further research.

Increasing amount of scientific publications makes it difficult to conduct a comprehensive review and objectively compare results of previous researches. In some areas of research it is also difficult to extract regularities without computer aid due to complexity of experimental setup and results. Cancer treatment using dendritic cell vaccines is such an area. In this paper we describe a framework for semi-automatic information extraction and further analysis. We also present a case study in the field of dendritic cell vaccination and the corresponding experimental results, which include analysis of separability, classification and regression quality evaluation and cause relations mining.