Extractive document summarization using an adaptive, knowledge based cognitive model

Abstract

Document summarization involves identifying the salient text in a document and creating a representative summary. The event-index cognitive model describes the human cognitive processes involved in generating situational models from a given text to comprehend that text. This paper proposes an adaptive, knowledge based event-index cognitive model that creates an extractive summary for a given document. The proposed cognitive model uses the hierarchical human memory model and emotion to create the extractive summary. The performance of the proposed cognitive model was compared with the existing state-of-art methods using the DUC (Document Understanding Conference) 2001 dataset and the ROUGE (Recall-Oriented Understudy for Gisting Evaluation) summary evaluation tool. Under ROUGE-N, ROUGE-L, ROUGE-S and ROUGE-SU evaluations, the proposed cognitive model for document summarization achieved an improvement of 25%, 12%, 24% and 18% in mean F-measure values. The results are statistically verified as significantly better than existing state-of-art methods using one way ANOVA with post-hoc Tukey-HSD test. In addition, this paper discusses the possible future research directions in document summarization based on the proposed cognitive model.