Latent Semantic Analysis in Automatic Text Summarization: A State of the Art analysis

Abstract

Increasing availability of information in the web and its ease of access necessitates the need for efficient and effective automatic text summarization. Automatic text summarization condenses the source text (a single document or multiple documents) into a compact version preserving its overall meaning and information content. Till now, researchers have employed different approaches for creating well-formed summaries. One of the most popular methods is the Latent Semantic Analysis (LSA). In this paper, various prominent works to produce extractive and abstractive text summaries based on different variants of LSA algorithm are reviewed, analysed and compared.