Statistical mechanisms of the subject domains associative portraits formation on the basis of big natural language texts for the systems of knowledge extraction

Associative relations between terms, concepts and other elements of natural language play an important role in decision of a wide variety of application tasks including intelligent texts processing, knowledge extraction, and management comprizing the formation of knowledge bases and semantic information retrieval. The paper presents the methods of automatic establishment of the associative relations between terms and concepts in the texts from Internet and creation of subject domains associative portraits designed for the tasks of intelligent systems development. An associative portrait of a subject domain (APSD) is a dictionary of the meaningful support terms and word combinations interconnected by associative relations. It is essential that the APSD are constructed automatically on the basis of statistical analysis of big volumes of texts. The theoretical impact of the proposed method consists in the use of statistics, corpus linguistics, and distributional semantics for processing big volumes of natural language texts which are dynamically updated and enriched in the Internet for constructing the model of a subject domain in the form of APSD.