Summarize the following text on the main techniques used for text summarization:

Text summarization is the process of creating a concise and precise summary of a longer piece of text while focusing on the major points covered and leaving out unnecessary details. There are two main approaches to automatic text summarization: extractive and abstractive summarization.

Extractive summarization involves identifying the most important sentences or phrases from the original text and concatenating them to produce the summary. This method preserves the exact words and phrases used in the source text. Common techniques include scoring sentences based on statistical and linguistic features, like word/phrase frequency, position, length, and cue words.

Abstractive summarization, on the other hand, aims to produce a summary that captures the essence of the source text, but using novel words and phrases not found in the original. This approach involves interpreting the semantic meaning of the text and generating new sentences to convey the key points. It often employs advanced natural language processing and generation techniques, such as parsing, semantic representation, and language modeling.

Overall, extractive summarization is considered simpler to implement but may lack coherence and fail to capture the overall meaning. Abstractive summarization is more challenging but can potentially generate more concise and fluent summaries. Both approaches have their advantages and are actively researched in the field of natural language processing.
Summarize the following text on the main techniques used for text summarization:

Text summarization is the process of creating a concise and precise summary of a longer piece of text while focusing on the major points covered and leaving out unnecessary details. There are two main approaches to automatic text summarization: extractive and abstractive summarization.

Extractive summarization involves identifying the most important sentences or phrases from the original text and concatenating them to produce the summary. This method preserves the exact words and phrases used in the source text. Common techniques include scoring sentences based on statistical and linguistic features, like word/phrase frequency, position, length, and cue words.

Abstractive summarization, on the other hand, aims to produce a summary that captures the essence of the source text, but using novel words and phrases not found in the original. This approach involves interpreting the semantic meaning of the text and generating new sentences to convey the key points. It often employs advanced natural language processing and generation techniques, such as parsing, semantic representation, and language modeling.

Overall, extractive summarization is considered simpler to implement but may lack coherence and fail to capture the overall meaning. Abstractive summarization is more challenging but can potentially generate more concise and fluent summaries. Both approaches have their advantages and are actively researched in the field of natural language processing.
user
The text discusses two main techniques for automatic text summarization: extractive and abstractive summarization. Extractive summarization identifies and concatenates the most important sentences from the original text, while abstractive summarization interprets the semantic meaning and generates novel sentences to convey the key points. The text notes that extractive summarization is simpler but may lack coherence, whereas abstractive summarization is more challenging but can produce more concise and fluent summaries.
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: Could you summarize what this article says are ways to use essential oils? The article says:
AROMA DIFFUSER
This method is beneficial for mood enhancement and upliftment.  It disinfects the air and can boost immunity through inhalation.  Fill the bowl with water, add 5-15 drops and enjoy
STEAM INHALATION
This method is used mainly for upper respiratory problems such as bronchial and sinus congestion, colds, coughs, and influenza.  Fill a large bowl with boiling water and add three drops of essential oil.  Lean over the bowl with your eyes closed and a towel over your head and inhale the steam for 5-10 minutes.
VAPORIZER
An effective decongesting method for respiratory conditions.  Add from 3 to 9 drops of essential oil to the water of the vaporizer.  Run overnight.
Response: Three ways to use essential oils include in an aroma diffuser, via steam inhalation, and in a vaporizer. 

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.
