Abstract
Text Summarization is a process where a huge text file is converted into summarized version which will preserve the original meaning and context. The main aim of any text summarization is to provide a accurate and precise summary. One approach is to use a sentence ranking algorithm. This comes under extractive summarization. Here, a graph based ranking algorithm is used to rank the sentences in the text and then top k-scored sentences are included in the summary. The most widely used algorithm to decide the importance of any vertex in a graph based on the information retrieved from the graph is Graph Based Ranking Algorithm. TextRank is one of the most efficient ranking algorithms which is used for Web link analysis that is for measuring the importance of website pages. Another approach is abstractive summarization where a LSTM encoder decoder model is used along with attention mechanism which focuses on some important words from the input. Encoder encodes the input sequence and decoder along with attention mechanism gives the summary as the output.
Highlights
Summary created with the help of main points which are the sentences form the original document with the help of a software is known as automatic summarization
The previous proposed systems use Bag of Words (BOW), which is extended in this model to Vector of sentences, so as to achieve the extractive nature of the model
The accuracy varies as the sentences in the summary may or may not be much reliable
Summary
World Wide Web provides huge variety of data from which the user can find useful data according to their needs and purpose. It is highly beneficial to use an efficient text summarization in this hectic world so that only user required and useful data is provided to the user in a lesser time. Manual summarization of documents and webcontents is too time-consuming this paved the need for automatic summarization [8, 10] of text documents and webcontents. Summary created with the help of main points which are the sentences form the original document with the help of a software is known as automatic summarization. Text Summarization can be classified into different categories:
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