Read the following details about query-based text summarization and summarize the main points concisely:

Query-based text summarization systems aim to generate summaries that are focused specifically on answering a particular user's information need or query, rather than providing a general overview of the content. These systems take as input a body of text data along with a query, representing the user's information requirements. The summarization model must then extract or generate relevant summary content that directly addresses the query, filtering out extraneous information that does not pertain to answering it. User queries can range from simple keyword searches to more complex natural language questions. Query-based summarizers may leverage techniques like semantic parsing of the query, retrieval of relevant passages, and ranking sentences by degree of query relevance to produce focused summaries tailored to the specific user's information need.
Read the following details about query-based text summarization and summarize the main points concisely:

Query-based text summarization systems aim to generate summaries that are focused specifically on answering a particular user's information need or query, rather than providing a general overview of the content. These systems take as input a body of text data along with a query, representing the user's information requirements. The summarization model must then extract or generate relevant summary content that directly addresses the query, filtering out extraneous information that does not pertain to answering it. User queries can range from simple keyword searches to more complex natural language questions. Query-based summarizers may leverage techniques like semantic parsing of the query, retrieval of relevant passages, and ranking sentences by degree of query relevance to produce focused summaries tailored to the specific user's information need.
user
Query-based text summarization systems generate summaries focused on answering a specific user query, rather than giving a general overview. The key points are: 1) These systems take text data and a user query as input, representing the user's information need. 2) The summarization model extracts or generates relevant content to directly address the query, filtering out extraneous information. 3) Techniques like semantic parsing of the query, retrieving relevant passages, and ranking sentences by query relevance are used to produce summaries tailored to the specific information need.
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: Please read this text: 

People consume information in lots of different ways: visually, audibly, through text, and sometimes all three at once. Search engine algorithms like Google’s are advancing to reflect this experience for users. No longer will the algorithms just look at web pages as a single piece of text content. Google will look at all the ways real people consume information: text, images, videos, infographics, tables, charts, and interactive elements that make up a piece of content.

In recent years, we saw the rise of visual search – particularly in image-heavy industries like travel and tourism or ecommerce. Moving into 2023, Google will expand its foothold in multisearch and multisearch near me. 

What does it say about multi-format content in a brief summary?
Response: The text says that people prefer content in different forms like audio, video, or text format. As a result, Google plans to advance the multi-search function and page search algorithms accordingly. 

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.
