Graph Based Text Summarization using NER and POS

Text summarization is the process of extracting needed information from the source text and to present that information to the user in the form of summary. It is not possible for human beings to summarize large documents manually. Automatic summarization provides the required solution as well as challenging task because it requires deep analysis of text. There are two types of summarization: Extractive summarization and Abstractive summarization. The Extractive summaries are produced by extracting the whole sentences from the source text. Abstractive summaries are produced by reformulating sentences of the source text. This paper is about a survey of text summarization techniques for various Indian regional languages like Hindi, Punjabi, Tamil Kannada and Bengali. The proposed system is based on English language text summarization in which Naming entity reorganization and Part Of speech is used for feature extraction and graph is generated for text summarization.