Hybrid Text Summarization: A Survey

Abstract

Text summarization is the technique of shirking the original text document in such a way that its meaning is not altered. Summarization techniques have become important for information retrieval as large volumes of data are available on Internet and it is impossible for a human to extract relevant information from enormous amount of data in a time-bound situation. Thus, automatic text summarizer is a tool for reducing the information available on Internet by providing nonredundant and salient sentence extracted from a single or multiple text documents. Text summarization has two approaches: extractive and abstractive. Extractive approach generates the summary by selecting subsets of words, sentences, and phrases of text documents whereas abstractive approach understands the main idea of the document and then represents that idea in a natural language using natural language generation technique to create summaries. This paper represents a Survey of Automatic Hybrid Text Summarization.