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: In short, what does creating zones do for a home? Use this text:
Create Zones
Zoned living room 
 Jenny Davis
Native New Yorker and designer Jenny Davis knows a thing or two about small space living is her thing, learning make her home work for her growing family.

"Creating zones within a room can make it look and feel bigger, as long as it’s done right," she says. "Placing furniture perpendicular to or off the wall is a great way to do this. I’ve used this tactic in our kids’ bedroom where I floated a table in the back of the room to define and anchor the art area. And, in the living room, I use a toy hub to divide the kids’ play area and our living room, and it has an open back so it doesn’t minimize light or how far the eye can see.

Davis says that creating zones can help you make the most of your space, no matter the size, as well as making your home look and feel bigger.
Response: Creating zones can utilize the space for different needs and make the room feel bigger.

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.

Summarize the following text on summarization techniques:

Summarization is the process of condensing a larger body of text into a concise and comprehensive summary. It serves to capture the most crucial information and main ideas within the original text. Various techniques exist for effective summarization, including extraction and abstraction.

Extraction-based summarization involves selecting and reproducing the most significant sentences or phrases from the original text. This approach leverages algorithms and statistical methods to identify and extract the key content elements. Extractive summarization is computationally efficient but may lack context or coherence at times.

In contrast, abstraction-based summarization involves generating entirely new sentences that capture the essence of the original text. This approach requires a deeper understanding of the text's meaning and the ability to restructure and paraphrase the content. Abstractive summarization often employs advanced natural language processing techniques, such as semantic analysis and language generation models. While more complex, it can produce more coherent and concise summaries.

Hybrid approaches combine elements of both extraction and abstraction, leveraging the strengths of each technique. Additionally, advanced summarization methods incorporate techniques like topic modeling, graph-based algorithms, and deep learning models to improve the quality and accuracy of summaries.

Effective summarization is crucial in various domains, including academia, journalism, legal documentation, and business intelligence. By condensing lengthy texts into concise summaries, summarization aids in information comprehension, knowledge dissemination, and decision-making processes.
user
Summarization involves condensing a larger text into a concise summary, capturing the main ideas. Extraction-based summarization selects and reproduces key sentences or phrases, while abstraction-based summarization generates new sentences that capture the essence. Hybrid approaches combine both techniques, and advanced methods incorporate techniques like topic modeling and deep learning to improve summary quality and accuracy.
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