Technology has flooded human being with information, we just need to dial the text and search a complete heap of data which is later segregated according to its usefulness. However, this segregation is very difficult and involves usage of a brilliant mind. Here comes the use of Automatic Text Summarization (ATS), which condenses this information into useful information, saving user's time and attracts a complete ground for research work in
Natural Language Processing (NLP). In this paper various statistical and linguistic features for a sentence are discussed. Based upon these features, weight is assigned to every sentence. According to this weight, importance of a sentence is decided into the summary. The summary generated by this method covers maximum theme with less redundancy. This work is done for the Hindi language .
Hindi text summarization, natural language processing, statistical and linguistic features, SOV qualification