Abstract. From the very begin of symbol of life men has tried to make the life easier than their initial and nowadays they are very hopeful to make the life and it’s living component is more user friendly than before. So the purpose of the study is to generate a concise document description that is more revealing than a title but short enough to be absorbed in single glance . The initial goal is to make a gist of a paragraph with the help of computer. This includes ontology, natural language processing(NLP), automatic text summarization.And the capital aspect is to accomplish the basis of the argument as different as possible, and additionally plan to accommodate adaptation allotment here. Automatic text summarization has accepted a great deal…show more content… There are so many applications on natural language processing these are: Automatic text summarization translation, recognition etc[1]. Text summarization is one of the dynamic sector of NLP. Automatic summarization is the process of reducing a text document with a computer program in order to create a summary that mantain the most important points of the original document[2]. A summarizer is a system that generate a brief representation of its inputs for user consumption. There are two types of summarization first abstraction and second extraction. Automated text summarization is a complicated task which involves deep NLP capacities Automatic text summarization related with mathematics, robotics, and Electrical engineering.[1]Some tool and techniques are available for automatic text summarization these are Lexical chain analysis machine learning techniques Semantic and discourse analysis , Knowledge-based approaches and tools for NLP . In these methods there are some several problems these are: Inaccurate summarization, Pending problem, no control in length, Sentence granularity, We are able to build a new automated text summarization system where maximum control in length, Reduce pending problem, the output will be much efficient from previous system and accuracy rate will be better than…show more content… In this method there are some several problems these are: Inaccurate summarization,Pending problem,no control in length,Sentence granularity.The initial goal of this research is to make an efficient and effective tool[2][9]which is able to summarize large documents quickly.This research represents a linear time algorithm for counting lexical chains which is a method of receiving the ”philosophy of language” of a document.This method is compared to previous,less workable methods of lexical chain extraction.For automatic text summarization[2] they used a techniques which is lexical chains analysis.They used some new algorithm which are Word Net thesaurus, a part-of-speech tagger,shallow parser for nominal groups,and a segmentation algorithm.There are four step to proceed Summarization such as,the original text is segmented,lexical chains are constructed,strong chains are identified and significant sentences are extracted.In their procedure some problem occured these are panding