Question 1 of 30
A company is developing a customer support chatbot using Azure Bot Services. The chatbot needs to handle multiple intents, including FAQs, order tracking, and technical support. The development team is considering using the Language Understanding (LUIS) service to enhance the chatbot\'s ability to understand user queries. They want to ensure that the bot can accurately identify intents and extract relevant entities from user input. What is the best approach to optimize the performance of the LUIS model for this scenario?
Train the LUIS model with a diverse set of utterances for each intent and regularly update it with new data based on user interactions.
Use a single, generic utterance for each intent to simplify the training process and reduce complexity.
Limit the number of intents to only the most common queries to avoid overwhelming the model.
Rely solely on pre-built LUIS models without customizing them for the specific needs of the chatbot.

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