Extractive summarization based cognitive aspects of human mind for narrative text

This study describes a text summarization system based on cognitive models. The underlying theory is about comprehension and is used to explain comprehending narrative texts. Majority of previous methods have been used statistical approaches for summarization, and this method is different as it tries to build a system based on a cognitive theory and not statistical methods. Main principle of model is that as humans read a text, they will make a mental image based on temporality, causality, intentionality, protagonists, and place. Proposed system extracts five features for each sentence and identifies the most important sentences based on the five features. The results obtained from this method were satisfactory and comparable from modern statistical techniques.