Summarize the following text about summarization techniques:

Text summarization is the process of creating a concise and precise summary of a longer piece of text. It aims to capture the key points and essential information while removing redundant or unnecessary details. There are two main approaches to text summarization: extractive and abstractive.

Extractive summarization involves selecting the most important sentences or phrases from the original text and combining them to form the summary. This method preserves the original wording and phrasing. Common techniques for extractive summarization include using statistical and linguistic features to score and rank sentences, as well as graph-based methods that analyze the relationships between sentences.

Abstractive summarization, on the other hand, generates entirely new sentences to convey the most important information from the source text. This approach involves understanding the semantic meaning of the text and rephrasing it in a concise manner. Abstractive summarization typically relies on advanced natural language processing techniques, such as deep learning models trained on large datasets of text and summaries.

Evaluation of text summaries is a crucial aspect of summarization systems. Commonly used evaluation metrics include ROUGE scores, which measure the overlap between the generated summary and reference summaries created by humans. Other factors, such as coherence, grammaticality, and informativeness, are also considered when assessing the quality of summaries.
Summarize the following text about summarization techniques:

Text summarization is the process of creating a concise and precise summary of a longer piece of text. It aims to capture the key points and essential information while removing redundant or unnecessary details. There are two main approaches to text summarization: extractive and abstractive.

Extractive summarization involves selecting the most important sentences or phrases from the original text and combining them to form the summary. This method preserves the original wording and phrasing. Common techniques for extractive summarization include using statistical and linguistic features to score and rank sentences, as well as graph-based methods that analyze the relationships between sentences.

Abstractive summarization, on the other hand, generates entirely new sentences to convey the most important information from the source text. This approach involves understanding the semantic meaning of the text and rephrasing it in a concise manner. Abstractive summarization typically relies on advanced natural language processing techniques, such as deep learning models trained on large datasets of text and summaries.

Evaluation of text summaries is a crucial aspect of summarization systems. Commonly used evaluation metrics include ROUGE scores, which measure the overlap between the generated summary and reference summaries created by humans. Other factors, such as coherence, grammaticality, and informativeness, are also considered when assessing the quality of summaries.
user
The given text discusses the process of text summarization, which involves creating a concise summary from a longer piece of text. It outlines the two main approaches: extractive summarization, where important sentences or phrases are selected and combined from the original text, and abstractive summarization, which generates new sentences to convey the key information. The text also mentions techniques used in each approach, such as statistical and linguistic features for extractive summarization, and deep learning models for abstractive summarization. Finally, it highlights the importance of evaluating summaries using metrics like ROUGE scores and factors like coherence and informativeness.
assistant
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: Sum up the tips Joanna gives in the following article.

The article:
Give the shower curtain some texture

Joanna uses a ruffled white shower curtain for this bathroom, which she points out how this will make a statement in such a small space. However, choosing lighter colors still makes the space feel bigger.

Add extra lighting

One of the things that Joanna encourages people to do is make room in the budget for extra lighting. In the bathroom she designed, Joanna uses a vanity as well as an antique chandelier to give the space plenty of light. And what does light do? “Light makes things feel bigger so that’s the trick,” said Joanna. Learn what effortless tasks clutter-free people do every day.

Add a vanity mirror

Along with the ruffled shower curtain, Joanna says a vanity mirror can make a huge statement in such a small space. In the bathroom she worked on, she repainted an antique mirror she found, leaving some of the wood unpainted to give it the distressed look.

Since the countertop is smaller, Joanna decided to use a raised vessel sink to make the bathroom feel larger. She says this helps to give the sink and counter the illusion that it’s bigger than it actually is.
Response: Joanna suggests using a textured shower curtain to make a statement in a small space and that adding extra lighting because light makes rooms feel larger. Also adding a vanity mirror will make a statement in that small bathroom.

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.
