A News Summarization System using Fuzzy Graph Based Document Model
Deepa. C A, Reghu Raj. P C
International Journal of Computational Linguistics Research, Vol. 5, No. 3, 2014.
DOI: 
Link: http://www.dline.info/jcl/fulltext/v5n3/1.pdf
Abstract:
This paper describes a news summarization system using the Fuzzy Graph based Document Model. News
articles are modelled as fuzzy graphs whose nodes are sentences and edges are weighted by the fuzzy similarity measure between the sentences. The similarity between sentences is in between 0 and 1. Centrality of the graph retrieves important
sentences. The proposed system produces summaries by Eigen value convergence of the similarity matrix. The summaries are evaluated based on the human generated summaries in DUC 2007 data set. The resultd show fuzzy graph based approach for
news summarization using Eigen value analysis are quite encouraging. It shows high correlation with human generated summaries.