Text Summarization within the Latent Semantic Analysis Framework: Comparative Study

Abstract

It is very difficult for human beings to manually summarize large documents of text. Text summarization solves this problem. Nowadays, Text summarization systems are among the most attractive research areas. Text summarization (TS) is used to provide a shorter version of the original text and keeping the overall meaning. There are various methods that aim to find out well-formed summaries. One of the most commonly used methods is the Latent Semantic Analysis (LSA). In this review, we present a comparative study among almost algorithms based on Latent Semantic Analysis (LSA) approach. General Terms Natural Language Processing (NLP).