Knowledge Representation for an Automated Normalized Answers Assessment System, Based on Text Comprehension Theories

In the present work, a knowledge representation of Computer Networks technical text, according to the Denhiere-Baudet text comprehension model, is presented. The semantic relations among units and events of a technical text can be expressed by structures, as microstructure and macrostructure. Furthermore, the explicit and implicit knowledge representation, and the micro and macrostructure representation of the functional system operations, depicted in this text, is provided. The presented methodology can support automated reasoning, through the knowledge representation, which leads to automated knowledge extraction from a technical text, and, subsequentially, to automated normalized answers assessment.