Automatic Text Summarization using Wu-Palmer Measure and Graph based Sentence Selection

In this paper, an extraction based text summarization methodology is proposed that aims to overcome issues faced with traditional extraction based summarizers using a combination of testing semantic similarity using the Wu-Palmer Measure and a graph-based sentence selection scheme for single document summarizations. The proposed approach is not only independent of context, syntax and language but also promotes shorter summaries via its sentence selection scheme. This method has been tested using the standard Reuters-21578 collection against widely used TextRank based summarizers and has shown promising results for single-document summarizations.