Classifying E-Commerce Search Queries at Scale: Finetuning a Transformer and Replacing the…
📰 Medium · Deep Learning
Learn how to classify e-commerce search queries at scale using a fine-tuned transformer and a two-level taxonomy classifier
Action Steps
- Fine-tune a transformer model for e-commerce search query classification
- Apply structural decomposition to improve model performance
- Implement a two-level taxonomy classifier to handle complex queries
- Test and evaluate the model using a large dataset of search queries
- Configure the model to handle out-of-vocabulary words and rare queries
Who Needs to Know This
Data scientists and machine learning engineers on an e-commerce team can benefit from this approach to improve search query classification and enhance customer experience
Key Insight
💡 Fine-tuning a transformer model with structural decomposition and a two-level taxonomy classifier can significantly improve e-commerce search query classification accuracy
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🛍️ Classify e-commerce search queries at scale with fine-tuned transformers and two-level taxonomy classifiers! 💡
Full Article
How structural decomposition, encoder finetuning, and a few counterintuitive findings shaped a two-level taxonomy classifier for product… Continue reading on Medium »
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