Summarize the following text about the different types and techniques of summarization:

Summarization can take various forms and employ different techniques, depending on the purpose and context. One common approach is extractive summarization, which involves selecting and combining the most salient sentences or phrases from the original text to create a summary. This method is particularly useful for condensing factual information and preserving the original language and tone. Extractive summarization can be rule-based, relying on predefined heuristics or algorithms to identify important sentences, or it can be based on machine learning models trained on large datasets of summarized texts.

In contrast, abstractive summarization involves generating entirely new sentences that capture the essence of the source material. This approach requires a deeper understanding of the content and often employs natural language processing techniques, such as semantic analysis and language generation. Abstractive summaries can be more concise and coherent, as they are not constrained by the original text's structure or phrasing. However, they also pose a greater risk of introducing inaccuracies or omitting important details.

Another type of summarization is query-based or topic-focused, where the summary is tailored to address specific questions or topics of interest. This approach is particularly valuable in information retrieval systems, allowing users to quickly obtain relevant information without sifting through extensive content. Additionally, multi-document summarization involves synthesizing information from multiple sources into a unified summary, which is useful for literature reviews, research reports, and other contexts that require integrating information from diverse sources.

Regardless of the specific technique employed, effective summarization requires careful consideration of the target audience, the intended purpose, and the appropriate level of detail and focus. It may involve selecting and organizing content, condensing language, or generating new text – all while preserving the core meaning and intent of the original material.
Summarize the following text about the different types and techniques of summarization:

Summarization can take various forms and employ different techniques, depending on the purpose and context. One common approach is extractive summarization, which involves selecting and combining the most salient sentences or phrases from the original text to create a summary. This method is particularly useful for condensing factual information and preserving the original language and tone. Extractive summarization can be rule-based, relying on predefined heuristics or algorithms to identify important sentences, or it can be based on machine learning models trained on large datasets of summarized texts.

In contrast, abstractive summarization involves generating entirely new sentences that capture the essence of the source material. This approach requires a deeper understanding of the content and often employs natural language processing techniques, such as semantic analysis and language generation. Abstractive summaries can be more concise and coherent, as they are not constrained by the original text's structure or phrasing. However, they also pose a greater risk of introducing inaccuracies or omitting important details.

Another type of summarization is query-based or topic-focused, where the summary is tailored to address specific questions or topics of interest. This approach is particularly valuable in information retrieval systems, allowing users to quickly obtain relevant information without sifting through extensive content. Additionally, multi-document summarization involves synthesizing information from multiple sources into a unified summary, which is useful for literature reviews, research reports, and other contexts that require integrating information from diverse sources.

Regardless of the specific technique employed, effective summarization requires careful consideration of the target audience, the intended purpose, and the appropriate level of detail and focus. It may involve selecting and organizing content, condensing language, or generating new text – all while preserving the core meaning and intent of the original material.
user
Summarization can take different forms, including extractive summarization (selecting salient sentences/phrases from the original text), abstractive summarization (generating new sentences to capture the essence), query-based or topic-focused summarization (tailored to specific questions/topics), and multi-document summarization (synthesizing information from multiple sources). Each approach employs different techniques, such as rule-based or machine learning methods for extractive summaries, natural language processing for abstractive summaries, and careful consideration of the audience, purpose, and desired level of detail across all types.
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: Condense the following piece of history into one or two sentences for me:

Before 1895, the area corresponding to modern-day South Gyeongsang Province was part of Gyeongsang Province, one of the Eight Provinces of Korea during the Joseon dynastic kingdom. In 1895, southern Gyeongsang was replaced by the districts of Jinju in the west and Dongnae (modern-day Busan) in the east. In 1896, they were merged to form South Gyeongsang Province.

The provincial capital was originally at Jinju; it moved in 1925 to Busan.During the Japanese rule of Korea, the province was known as Keishōnan-dō. In 1948, South Gyeongsang Province became part of South Korea. In 1963, Busan separated from South Gyeongsang Province to become a Directly Governed City (Jikhalsi). In 1983, the provincial capital moved from Busan to Changwon.
Response: Modern-day South Gyeongsang Province used to be part of Gyeongsang Province until 1895, with its current provincial capital being Changwon after changing twice. 

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.
