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Related Questions
- Can you describe the role of prompt engineering in increasing the transparency of recommendation algorithms?
- How do explainable AI techniques, such as attention weights, contribute to improving the interpretability of recommendation systems?
- What are some common challenges in applying prompt engineering to improve the explainability of recommendation systems in e-commerce?
- Can you discuss the impact of using natural language processing (NLP) to generate human-readable explanations for recommendation system outputs?
- How do prompt-based approaches, such as input-output pair examples, aid in the development of more transparent and explainable recommendation systems?
- What are some potential applications of prompt engineering in improving the explainability of recommendation systems in various e-commerce domains?
- Can you explain how prompt engineering can help bridge the gap between the black box nature of deep learning models and the need for transparent and interpretable recommendations in e-commerce?
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