This paper introduces a system that incorporates several strategies based on scientific models of how the brain records and recovers memories. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architecture that can be adapted to any language. A special case is studied and tested regarding the Spanish language. The applications of this proposal are vast because, in general, information such as text way, reports, emails, and web content, among others, is considered unstructured and, hence, the repositories based on SQL databases usually do not handle this kind of data correctly and efficiently. The conversion of unstructured textual information to structured one can be useful in contexts such as Natural Language Generation, Data Mining, and dynamic generation of theories, among others.

This paper introduces an abstract system for converting texts into structured information. The proposed architecture incorporates several strategies based on scientific models of how the brain records and recovers memories, and approaches that convert texts into structured data. The applications of this proposal are vast because, in general, the information that can be expressed like a text way, such as reports, emails, web contents, etc., is considered unstructured and, hence, the repositories based on a SQL do not capable to deal efficiently with this kind of data. The model in which was based on this proposal divides a sentence into clusters of words which in turn are transformed into members of a taxonomy of algebraic structures. The algebraic structures must comply properties of Abelian groups. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architecture that can be adapted to any language. A special case is studied, this deals with the Spanish language. The developed abstract system is a framework that permits to implements applications that convert unstructured textual information to structured information, this can be useful in contexts such as Natural Language Generation, Data Mining, dynamically generation of theories, among others.