Finding comparatively important concepts between texts

Finding important concepts is a common task in requirements engineering. For example, it is needed when building models of a domain or organising requirements documents. Since a lot of information is available in textual form, methods to identify important concepts from texts are potentially useful. Traditional methods for finding important concepts from texts rely on the assumption that the most frequent concepts are the most important. We present an approach that does not depend on this assumption. It makes use of two texts to find important concepts comparatively. We show that this approach is viable. It discovers concepts similar to those found by traditional approaches as well as concepts that are not frequent. Finally, we discuss the possibility of extending this work to requirements classification.