Abstract
Deepening prose comprehension involves understanding the relation among the prose concepts and reading external references. In this paper, we propose an interesting system which mimics the human reading process. Given a prose, the system discovers the relevant parts from relevant references that connect and illuminate a set of learnable concepts from the prose by adding new familiarity meaningful knowledge paths among them. We present a computational evaluation model to measure the acquired knowledge and the prose learning process by the system. We present an experiment, which uses Wikipedia articles as an external reference consultations to comprehend prose. The performance analysis shows that the system succeeded in connecting the concepts by discovering the relation among them and increases the learning process on prose comprehension.