AUTOMATED MIND MAP GENERATION FROM NEWS TEXTS BASED ON LINK GRAMMAR
This paper is devoted to the problem of extracting key entities from the article's text and representation of its content in a compressed format - so-called mind map. Particular attention is paid to text parsing based on link grammar. The main advantages of this approach are described. The paper presents a general methodology and appropriate software of text to mind map conversion, which includes initial stages of text analysis, dependency tree drawing and transforming it into a multi-level mind map with the possibility of replacing map's entities by the relevant picture.