A novel evolutionary connectionist text summarizer (ECTS)

Authors:
Rajesh S. Prasad;U. V. Kulkarni;Jayashree R. Prasad
Affiliations:
Department of Computer Engineering, Vishwakarma Institute of Technology, Pune, India;Academics, SGGS Institute of Technology, Nanded, India;Department of Computer Engineering, Vishwakarma Institute of Technology, Pune, India
Venue:
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Year:
2009

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Abstract

As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance.