Multi-Document and Multi-Lingual Summarization using Neural Networks

This system proposes Multi-lingual (Tamil and English) Multi-document summarization by neural networks. The system involves three steps. In first step, the sentences of the documents are converted into vector form. In the second step weight values are assigned to vector form based on sentence features. Depend on sentence weight value, single document summarization is done. The output of single document summarization is used as an input for multi-document Summarization. Final step is a sentence selection, in which output summary is selected based on the similarity and dissimilarity measures. Sentence similarity and dissimilarity measures are used to compare the sentences. From that, resultant summary is produced. The proposed system can be able to summarize both Tamil and English online news papers.

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