Text Summarization using Text Rank Algorithm and Microsoft Cognitive Services

The extractive summarization involves getting key phrases from the actual document and combining those key phrases to make a brief summary. Most used technique for extractive text summarization is sentence scoring. So, extractive summarization involves assigning saliency measure to some units of the documents and extracting those with highest scores to include in the summary of the document.Extractive text summarization methods can be classified into two: Supervised Learning methods and Unsupervised Learning methods.