Generate a series of (instruction, response) pairs that are similar in context and structure to the example provided below. Each pair should consist of a concise instruction followed by an appropriate, detailed response. The instruction should pose a clear task or question, while the response should provide a comprehensive answer or solution that could be understood by someone with a basic understanding of the subject.

Example pair: 
Instruction: Summarize the style of the poems mentioned in this paragraph:

But the sheer volume of artistic content available today has begun to blur the lines between syntax and symbolism. Since the Victorian era and especially during the Modernist movement, artists, authors, and poets had started to experiment with the bounds of their respective crafts. Poems like T.S. Eliot’s The Waste Land or E.E. Cummings’s anyone lived in a pretty how town is so linguistically fragmented as to become a mosaic of sound, a pointillistic array of images and ideas expressed less with logic and meaning than with mood and impression.
Response: T.S. Eliot and E.E. Cummings used words in a linguistically fragmented style, creating impressions and moods.

Your task is to generate more pairs that maintain this level of clarity and detail. The topic is Summarization. Write a long text of instruction by yourself, then summarize the given instruction in a response. Ensure that the responses are informative and accurate, suitable for an educational context. 

Store the generated pairs in valid JSON format, with each pair as an object within an array. Each object should have two key-value pairs: "instruction" and "response". For instance: 

{"contents": [{"instruction": "text", "response": "text"}, {"instruction": "text", "response": "text"}, ...]} 

Remember to maintain consistency in the format and ensure the generated pairs are diverse and cover a broad range of subjects. You must return the response in the asked format and you must not add any additional text in your response.

Explain the importance of text summarization in various applications and domains.
user
Text summarization has become increasingly important in various applications and domains due to the vast amount of textual data available. In information retrieval and search engines, summaries provide concise overviews of documents, enabling users to quickly assess relevance. In news and media, summaries help readers quickly grasp the key points of articles. In scientific research, summarization aids in literature reviews and knowledge discovery. In business and intelligence analysis, summaries facilitate understanding of large volumes of reports and documents. Additionally, summarization is useful for text compression, document clustering, and improving the efficiency of natural language processing tasks.
assistant