A Trigraph Based Centrality Approach Towards Text Summarization

As the electronic documents are increasing due to the revolution of information there is an urgent need for summarizing the text documents. From the previous works we observed that there is no generalized graph model for text summarization and low order ngrams could not preserve the contextual meaning. This paper focuses on an extractive based graphical approach for text summarization, based on trigrams and graph based centrality measure. Trigraph is generated and the centrality of the connected trigraph is taken to extract the important trigrams. A mapping is done between the original words and the trigrams to regain the link between the words. And after comparing the centrality from the graph, the summary is extracted. The ROUGE-SU4 F-measure obtained for the proposed approach is 0.036 which is significantly better than the previous approaches.