  In this article is analyzed technology of automatic text abstracting and
annotation. The role of annotation in automatic search and classification for
different scientific articles is described. The algorithm of summarization of
natural language documents using the concept of importance coefficients is
developed. Such concept allows considering the peculiarity of subject areas and
topics that could be found in different kinds of documents. Method for
generating abstracts of single document based on frequency analysis is
developed. The recognition elements for unstructured text analysis are given.
The method of pre-processing analysis of several documents is developed. This
technique simultaneously considers both statistical approaches to abstracting
and the importance of terms in a particular subject domain. The quality of
generated abstract is evaluated. For the developed system there was conducted
experts evaluation. It was held only for texts in Ukrainian. The developed
system concluding essay has higher aggregate score on all criteria. The
summarization system architecture is building. To build an information system
model there is used CASE-tool AllFusion ERwin Data Modeler. The database scheme
for information saving was built. The system is designed to work primarily with
Ukrainian texts, which gives a significant advantage, since most modern systems
still oriented to English texts
