Amazon researchers have developed KD-Boost, a knowledge distillation technique, to address the challenges of real-time semantic matching in web search and e-commerce product search. KD-Boost uses ground truth and soft labels from a teacher model to train low-latency, accurate student models. The technique has shown significant improvements in relevance, query-to-query matching, and product coverage.
Amazon Researchers Propose KD-Boost: A Novel Knowledge Distillation Algorithm Designed for Real-Time Semantic Matching
Web search and e-commerce product search rely on accurate real-time semantic matching. However, bridging the semantic gap between user queries and search results can be challenging. Amazon researchers have developed KD-Boost, a knowledge distillation technique that addresses these challenges and improves both product sourcing and query reformulation.
How KD-Boost Works
KD-Boost uses ground truth and soft labels from a teacher model to train low-latency, accurate student models. Pairwise query-product and query-query signals are used as soft labels, which are obtained through direct audits, user behavior research, and taxonomy-based data. Custom loss functions guide the learning process to ensure accurate representations of relevance and similarity.
Results and Benefits
Tests on e-commerce datasets have shown a significant improvement in ROC-AUC compared to direct training of student models. KD-Boost outperforms both state-of-the-art knowledge distillation benchmarks and teacher models. In simulated online A/B tests, KD-Boost has demonstrated increased query-to-query matching, improved relevance, and wider product coverage.
Practical AI Solutions for Middle Managers
If you want to leverage AI to evolve your company and stay competitive, consider using KD-Boost for real-time semantic matching. AI can redefine your way of work by automating customer interactions and improving sales processes. To get started with AI:
- Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
- Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
- Select an AI Solution: Choose tools that align with your needs and provide customization.
- Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
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