What is text summarization in natural language processing and how is it performed using extractive and abstractive approaches? How does extractive summarization select and combine important sentences from the original text? How does abstractive summarization generate new sentences to represent the meaning of the text? What are the key differences between these two techniques in terms of accuracy, complexity, and output quality? What are the common applications and challenges of extractive and abstractive summarization in real-world NLP systems?