Comprehensive and evolution study focusing on comparative analysis of automatic text summarization

Abstract

In the escalating trend of atomization and online information, text summarization bolster in perceiving textual information in the form of summary. It’s highly tedious for human beings to manually summarize large documents of text. In this paper, a study on abstractive and extractive content rundown strategies has been displayed. In Extractive Text Summarization it talk about TF-IDF, Cluster based, Graph theory, Machine learning, Latent Semantic Analysis (LSA) and Fuzzy logic approaches. Abstractive rundown techniques are ordered into two classes i.e. Structured based approach and Semantic based approach. In Structure Based approach it talk about Tree based, Template based, Ontology based, Lead & Phase based and Rule based method. In Semantic Based Approach it talks about Multimodal semantic, Informative item based and Semantic graph based method. The central idea of this method has been elaborated further, apart from idea, the advantages and disadvantages of these methods have been procured.