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: Please summarize:

TLS, short for Transport Layer Security, and SSL, short for Secure Socket Layers, are both cryptographic protocols that encrypt data and authenticate a connection when moving data on the Internet.

For example, if you’re processing credit card payments on your website, TLS and SSL can help you securely process that data so that malicious actors can’t get their hands on it.

So what’s the difference between TLS vs SSL?

Well, TLS is actually just a more recent version of SSL. It fixes some security vulnerabilities in the earlier SSL protocols.

Before you learn more about the specifics, it’s important to understand the basic history of SSL and TLS.

SSL 2.0 was first released in February 1995 (SSL 1.0 was never publicly released because of security flaws). Although SSL 2.0 was publicly released, it also contained security flaws and was quickly replaced by SSL 3.0 in 1996.

Then, in 1999, the first version of TLS (1.0) was released as an upgrade to SSL 3.0. Since then, there have been three more TLS releases, with the most recent release being TLS 1.3 in August 2018.
Response: TLS (Transport Layer Security) and SSL (Secure Socket Layers) are both cryptographic protocols that authenticate a connection and encrypt data on the Internet. If you're ver processed credit card payments on a website, you've used either TLS or SSL to do so to secure the process from bad actors. What's the difference between them? TLS is simply a more recent version of SSL, which fixes some security vulnerabilities that were in previous SSL protocols.

The basic history of SSL and TLS is as follows: SSL 2.0 was released in February 1995 (SSL 1.0 never made it to the public) Although SSL 2.0 had a public release, it contained security flaws as well and was replaced by SSL 3.0 in 1996. In 1999, TLS 1.0 was released as an upgrade to SSL 3.0. Three more TLS releases have since come. TLS 1.3 was released in August 2018.

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.

Please summarize the following text:

Text summarization is a crucial task in natural language processing that aims to generate concise and informative summaries from lengthy source documents. This process involves analyzing the text's content, structure, and semantics to identify the most relevant information, remove redundant or unnecessary details, and present the essential content in a coherent and readable manner. There are two main approaches to text summarization: extractive and abstractive. Extractive summarization selects and concatenates the most salient sentences or phrases from the original text to form the summary. This approach relies on scoring and ranking sentences based on features such as word frequency, position, and sentence length. Abstractive summarization, on the other hand, generates entirely new sentences that capture the essence of the text using advanced language generation techniques, such as semantic analysis, information fusion, and language modeling. This approach requires a deeper understanding of the text's meaning and the ability to paraphrase and synthesize information. Evaluation of summarization systems is a complex task, as it involves assessing the quality, informativeness, and coherence of the generated summaries. Various evaluation metrics have been proposed, including ROUGE (Recall-Oriented Understudy for Gisting Evaluation), which measures the overlap between the generated summary and reference human-written summaries.
user
Text summarization is a crucial NLP task that generates concise and informative summaries from lengthy documents. It involves analyzing content, structure, and semantics to identify relevant information, remove redundancies, and present essential content coherently. Extractive summarization selects and concatenates salient sentences/phrases based on scoring and ranking. Abstractive summarization generates new sentences capturing the essence using advanced language generation techniques and semantic understanding. Evaluation involves assessing quality, informativeness, and coherence against human-written summaries using metrics like ROUGE.
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