Automatic Text Summarization Based on Lexical-Semantic and Similarity Based On Sentence Embedding Model

Computer Engineering

The internet is made of online pages, news stories, status updates, blogs and much more. It is tough to browse through this material since it is unorganised and frequently discursive. Manual summary of big amounts of texts is arduous and mistake prone. Also, the findings in such form of summary may lead to diverse outcomes for a specific text. Thus, Automatic text summarization has become crucial owing to the massive rise of information and data. It identifies the most informative portion of text and creates summaries that highlight the primary objective of the provided content. It generates summary provided by summarising method which helps users to grasp the content of document instead for reading each and every individual document. So, the general purpose of Text Summarizer is to deliver the meaning of text in fewer words and phrases.

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