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Add Part 5, preview images, update series links

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thierrypdamiba
2026-01-30 16:36:18 -08:00
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qdrant-landing/content/articles/sparse-embeddings-ecommerce-part-1.md
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@@ -3,7 +3,7 @@ title: "Fine-Tuning Sparse Embeddings for E-Commerce Search | Part 1: Why Sparse
short_description: "Dense embeddings blur exact matches. Sparse embeddings keep the details that matter in e-commerce search."
description: "Part 1 of a 4-part series on fine-tuning SPLADE sparse embeddings for e-commerce search. Learn why sparse embeddings outperform BM25 and dense models for product search, how SPLADE works, and why Qdrant's native sparse vector support matters."
preview_dir: /articles_data/sparse-embeddings-ecommerce-part-1/preview
social_preview_image: /articles_data/sparse-embeddings-ecommerce-part-1/preview/social_preview.png
social_preview_image: /articles_data/sparse-embeddings-ecommerce-part-1/preview/social_preview.jpg
weight: -200
author: Thierry Damiba
author_link: https://github.com/thierrydamiba
@@ -18,6 +18,7 @@ category: practicle-examples
- [Part 2: Training on Modal](/articles/sparse-embeddings-ecommerce-part-2/)
- [Part 3: Evaluation & Hard Negatives](/articles/sparse-embeddings-ecommerce-part-3/)
- [Part 4: Specialization vs Generalization](/articles/sparse-embeddings-ecommerce-part-4/)
- [Part 5: From Research to Product](/articles/sparse-embeddings-ecommerce-part-5/)
---