An Approach for Summarizing Hindi Text Through a Hybrid Fuzzy Neural Network Algorithm

J. Anitha (), P. V. G. D. Prasad Reddy and M. S. Prasad Babu
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J. Anitha: Department of CSE, Dadi Institute of Engineering & Technology, Anakapalle, Vishakapatnam, India
P. V. G. D. Prasad Reddy: Department of CS & SE, Andhra University, Visakhapatnam, Andhra Pradesh, India
M. S. Prasad Babu: Department of CS & SE, Andhra University, Visakhapatnam, Andhra Pradesh, India

Journal of Information & Knowledge Management (JIKM), 2014, vol. 13, issue 04, 1-18

Abstract: Text summarization is one of the most discussed topic in the field in information exchange and retrieval. Recently, the need for local language based text summarization methods are increasing. In this paper, a method for text summarization in Hindi language is plotted with help of extraction methods. The proposed approach is uses three major algorithms, fuzzy classifier, neural network and global search optimization (GSO). The fuzzy classifier and neural network are used for generating sentence score. The GSO algorithm is used with the neural network, in order to optimize the weights in the neural network. A hybrid score is generated from fuzzy method and neural network for each input sentences. Finally, based on the hybrid score from fuzzy classifier and neural network, the summary of the given input records are generated. An experimental analysis of the proposed approach will subjected based on the evaluation parameters precision, recall. Later on experimental analysis are conducted on the proposed approach in order to evaluate the performance. According to the experimental analysis, the proposed approach achieved an average precision rate 0.90 and average recall rate of 0.88 for compression rate 20%. The comparative analysis also provided reasonable results to prove the efficiency of the proposed approach.

Keywords: Text summarization; GSO; crossover; ANN (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1142/S0219649214500361

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