Developing specialized knowledge bases for recursive parser of weakly connected originated natural language text information and Web-applications
Knowledge base for processing and structuring of natural - language information, which provides a recursive text parser, based on a new formal model of the structural level of organization of linguistic material,which provides a recursive scheme of organization that clearly defined an element of recursion - the basic semantic and syntactic structure, which is described by the extended model.
For a fuller this description used the metadata sets, that create a multidimensional metaindexes that describe not only the linguistic objects and fragments of text content of structural units, but which create additional metadata classification numbers, and on that basis in fact form the knowledge base. This allows parallel processing of text parts of the recursive text parser, increase the speed of text processing natural - language information and unify their processing.
Designing classifier knowledge base and develop an appropriate package of requests to search for all objects (text) or their fragments provide the ability to fully automate the collection and categorization of information from internal sources.
Offer a solution to the problem of automating the formation of a limited number of structural models due to a significant reduction in the structures of natural-language information representation, as well as by substitution of structural analysis - the analysis of parametric metadata models.