Text Summarization using Term Weights

Lot of work has already been done for automatic text summarization. In this paper we have given a novel statistical approach to summarize the given text. In our approach extraction of relevant sentences is done which can give the actual concept of the input document in a concise form. We rank each sentence in the document by assigning a weight value to each word of the sentence and a boost factor is also added to those terms which appear in bold, italic or underlined or any combination of these features. It helps us to extract more relevant sentences which will lead to a good summary of the given text.