Text Summarization for Multi Documents using Machine Learning

Automatic text summarization is one of the important challenges of natural language tasks. It will help the readers save time to get the important information from a lengthy document automatically. Automatic Text Summarization techniques aim to extract the fundamental information in documents. Multi-document summarization is useful when a user deals with a group of heterogeneous documents and wants to compile the important information present in the collection, or there is a group of homogeneous documents, taken out from a large corpus as a result of a query Summarization reduces the complexity of a document while retaining its important features The aim of multi- document summarization is to produce an abridged version which contains important information from a set of documents on the same topic. Multi-document summarization has gained popularity in many real world applications because signi�cant information can be obtained within a short time.