Explain the evaluation metrics commonly used to assess the quality of text summaries and their relative importance.
Explain the evaluation metrics commonly used to assess the quality of text summaries and their relative importance.
user
Several evaluation metrics are commonly used to assess the quality of text summaries, each focusing on different aspects of the summarization task. ROUGE (Recall-Oriented Understudy for Gisting Evaluation) is one of the most widely used metrics, which measures the overlap between the generated summary and reference summaries based on n-gram matching. Other metrics include BLEU (Bilingual Evaluation Understudy), which evaluates the fluency and adequacy of the summary, and METEOR (Metric for Evaluation of Translation with Explicit ORdering), which considers synonyms and paraphrasing in addition to n-gram matching. Human evaluation, where human annotators rate the summaries based on criteria such as informativeness, coherence, and overall quality, is also crucial for assessing the performance of summarization systems. The choice of evaluation metrics depends on the specific requirements of the task and the trade-offs between different aspects, such as content coverage, fluency, and conciseness.
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.
