A System for Converting and Recovering Texts Managed as Structured Information

Abstract

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.

E-contact facilitated by conversational agents reduces interethnic prejudice and anxiety in Afghanistan

“…4. Apply Natural Language Generation (NLG) 70 to the targeted nodes while posting specific messages for each. 5.…”