Literature Review of Automatic Single Document Text Summarization Using NLP

In the time of overloaded online information, automatic text summarization is especially demanded for salient information retrieval from huge amount electronic text. For the blessing of World Wide Web, the mass of data is now enormous in its volume. Researchers realized this fact from various aspects and tried to generate an automatic abstract of the gigantic body of data from the commencement of the last half century. Numerous ways are there for characterizing different approaches to passage recapitulation: extractive and abstractive from single or compound document, objective of content abridgement, characteristic of text summarization, level of processing from superficial to profound and sort of article's content. A significant précis is very much helpful in our day to day life which can save valuable time. The investigation was at first commenced naively on single document abstraction. In this paper, automatic single document text summarization task is addressed and different methodologies of various researchers are discussed from the very beginning of this research to this modern age. This literature review intends to observe the trends of abstraction procedure using natural language processing. Also some promising approaches are indicated and particular concentration is dedicated for the categorization of diversified methods from raw level to similar like human professionals, so that in future one can get precious direction for further analysis.