query expansion by prompting large language models
exileQuery expansion is a technique ud in information retrieval and natural language processing to improve the performance of a arch engine by adding additional terms or concepts to a ur's query. It aims to capture a broader range of relevant documents by expanding the original query.
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One effective way to perform query expansion is by prompting large language models such as GPT-3 or CTRL. The models have been trained on a diver range of text and can generate coherent and context-aware respons.
go onTo u query expansion with a large language model, you can follow the steps:
1. Formulate your original query: Start with a specific query that describes the information you are looking for. For example, if you are arching for "best restaurants in New York City," this would be your original query.
2. Provide context to the model: Begin by providing a brief introduction or context to the mo
del, explaining the purpo of your query and the topic you are interested in.不列颠哥伦比亚大学
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3. Ask the model to expand the query: Ask the model to propo additional terms, synonyms, related concepts, or contextually similar queries that can help expand your original query. You can prompt the model with a question like, "What are some other terms related to the best restaurants in New York City?"gianni versace
4. Generate suggestions for query expansion: The model will generate a respon that includes suggestions for expanding your query. The can be additional keywords, phras, or descriptions that can help you refine and broaden your arch.
wizard5. Incorporate the expanded query: Modify your original query by incorporating the suggestions provided by the model. You can add the new terms, synonyms, or concepts to your original query to create an expanded query that captures a wider range of relevant documents.德语入门
6. Retain the original query: It's important to retain the original query so that you can com
pare the results obtained with the expanded query to e if the retrieval performance has improved.
By leveraging large language models, query expansion becomes a more intuitive and context-aware process, helping urs to refine their queries and retrieve more relevant information.
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