A cognitive informatics framework for language understanding

For centuries, science and philosophy of human language have posited that language understanding is a logico-deductive process. In this paper, we argue that this is not necessarily the case, at least not for basic forms of understanding such as the ability to determine what a text document is about. We present a human-inspired Cognitive Informatics (CI) framework for basic language understanding that relies on the semantic relationship between words as embodied in conceptual knowledge stored in Long Term Memory (LTM). Short Term Memory (STM) limited capacity, neuromorphic spreading activations and neural decay are also contributing to meaning determination. A computational model implementing the framework shows the potential of the approach by establishing that the output of the model is as good as what humans generate.