Dense Semantic Graph and its Application in Single Document Summarisation

Semantic graph representation of text is an important part of natural language processing applications such as text summarisation. We have studied two ways of constructing the semantic graph of a document from dependency parsing of its sentences. The first graph is derived from the subject-object-verb representation of sentence, and the second graph is derived from considering more dependency relations in the sentence by a shortest distance dependency path calculation, resulting in a dense semantic graph. We have shown through experiments that dense semantic graphs gives better performance in semantic graph based unsupervised extractive text summarisation.