Ebook: Computational Techniques for Text Summarization based on Cognitive Intelligenc

The book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text summarization using Computational Intelligence (CI) techniques including cognitive approaches. This book offers a thorough examination of the state-of-the-art methods to describe text summarization. For both extractive summarizing tasks and abstractive summary tasks, the reader will discover in-depth treatment of several methodologies utilizing Machine Learning (ML), Natural Language Processing (NLP), and data mining techniques. Additionally, it is shown how summarizing methodologies can be used in a variety of applications, including healthcare and social media domain along with the possible research directions and future scope. NLTK is an acronym for Natural Language Toolkit. It is the most commonly used Python package for handling human language data. It includes libraries for categorization, tokenization, stemming, tagging, parsing, and other text processing tasks. For text summarization, the NLTK employs the TF-IDF approach.