一文搞懂AI大模型收录原理与关键技巧
The key to being prioritized and recommended by large AI models is not churning out content in bulk, but making information structured, scenario-based and authoritative. Core process: first understand model preferences → classify user intent → write scenario-based structured content → distribute stably across multiple channels → monitor, iterate and maintain. Below, Dabing shares the indexing principles and key techniques of major domestic large AI models (Doubao / Yuanbao / Deepseek).
Indexing preferences of different large AI models (key comparison: Doubao / Yuanbao / Deepseek)
1. Preferences and strategy for Doubao
Preferences: strong structure, answers placed upfront, authoritative citations (reports / experts);
Source bias: ByteDance ecosystem and content with media coverage / academic backing are prioritized;
Optimization tips: give a direct conclusion in the first 150–200 words; use tables / lists in the body; cite studies and reports to boost credibility;
Example: frame product highlights in a "problem → conclusion → key data" format – Doubao is much more likely to feature you as the top answer.
2. Preferences and strategy for Yuanbao
Preferences: WeChat ecosystem content (Official Accounts, Video Accounts, Tencent News) and in-depth long-form articles from portal sites (China.com, Kingsoft News, etc.);
Source bias: Tencent ecosystem accounts with stable updates and good engagement have a natural advantage;
Optimization tips: publish in-depth series content on Tencent platforms and sync short videos on Video Accounts to strengthen trust links within the ecosystem. Also pay attention to major portal websites.
3. Preferences and strategy for Deepseek
Preferences: industry knowledge graphs, structured content with clear entity relationships;
Source bias: official websites, industry sites and structured FAQ pages carry significant weight;
Optimization tips: build an entity chain of "brand → product → feature → case → certification", and use lists / tables / FAQs on the page.
4. Brief notes on other models
Wenxin: leans toward Baidu ecosystem resources (Baidu Baike, Baijiahao);
Kimi: broad sources, cites Zhihu, news and tech communities;
Practical advice: don’t put all your eggs in one basket. Cover multiple channels to adapt to the preference differences across models.
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