A Study on Different Multi-Document Summarization Techniques

In the present situation, the rate of increment of information is growing exponentially in the World Wide Web. As such, bifurcating genuine and noteworthy data from such a colossal size of information has turned into a dull issue. As of late, text summarization is viewed as one of the answers for ousting material data from multiple documents. In recent time, the method which proved to be most accurate for text summarization is Natural Language Processing. Content summary is a method of making an outline by diminishing the range of interesting report and relating basic information of extraordinary record. There is a huge rise in data augmentation on Internet. It increases the need of a highly optimise summary in less time. The system of efficient multi document summary generation can be a best achieving this goal. In this paper a survey on various approaches of summarization presented by the researcher is been discussed and studied.