What is Summarization?
Summarization is the process of creating a shorter version of text while preserving the most important information. It can be extractive (selecting key sentences) or abstractive (generating new sentences that capture meaning).
How It Works (quick)
- Extractive: Rank sentences by importance → select top spans.
- Abstractive: Encode full text → generate shorter output with a language model.
- Hybrid: Extract → refine with generation.
- Constraints: Control length, format (bullets), or aspect (e.g., pros/cons).
Why It Matters in E-commerce
- Product pages: Auto-generate concise highlights from long vendor descriptions.
- Reviews: Summarize thousands of reviews into aspect-based insights (fit, durability, sizing).
- Help content: Provide short answers for FAQs and AI assistants.
Best Practices
- Fine-tune models on domain-specific content.
- Always provide sources/snippets behind summaries.
- Use aspect-based summarization for reviews.
- Monitor for hallucinations; keep summaries factual.
- Add freshness weighting so summaries reflect current stock and reviews.
Summary
Summarization creates digestible content for faster understanding. In retail, it turns long descriptions and reviews into concise highlights that drive conversions.
