Extractive document summarization using an adaptive,knowledge based cognitive model |
| |
| Affiliation: | 1. Department of Computer Science and Engineering, PSG College of Technology, Coimbatore, India;2. Department of Computer Applications, PSG College of Technology, Coimbatore, India;1. Department of EIE, Dr. Mahalingam College of Engineering and Technology, Pollachi, Coimbatore, India;2. Department of EEE, Dr. Mahalingam College of Engineering and Technology, Pollachi, Coimbatore, India;1. EEE Dept, Kamaraj College of Engineering and Technology, Virudhunagar, Tamil Nadu, India;2. EEE Dept, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India;1. Pedagogical University of Cracow, Cryptography and Cognitive Informatics Research Group, Podchorążych 2 Street, PL-30-084 Kraków, Poland;2. Cryptography and Cognitive Informatics Research Group, AGH University of Science and Technology, 30 Mickiewicza Ave., 30-059 Kraków, Poland;1. Department of Electronics and Communication Engineering, Adhi College of Engineering and Technology, Kanchipuram, India;2. School of Information Technology and Engineering, VIT, Vellore, India;3. Department of Computer Science and Engineering, AdhiParasakthi Engineering College, Melmaruvathur, India;4. School of Computer Science and Engineering, RGM College of Engineering and Technology, Nandyal, A.P, India |
| |
| 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. |
| |
| Keywords: | Cognitive model Summarization Knowledge Memory Emotion |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
