openmlsys-zh/v1/zh_chapters/chapter_recommender_system/summary.md at 9c289782ccbb165ac8ad7c960ecffc12942a5560

mirror of https://github.com/openmlsys/openmlsys-zh.git synced 2026-05-12 11:06:53 +08:00

Files

Yeqi Huang d953030747 feat: add v1/v2 versioning with language selector (#494 )

* feat: add v1/v2 versioning and language selector for mdbook

- Copy current content to v1/ directory (1st Edition)
- Create v2/ directory with new TOC structure (2nd Edition) and placeholder chapters
- Add version selector (V1/V2) and language toggle (EN/ZH) in top-right nav bar
- Add build scripts: build_mdbook_v1.sh, build_mdbook_v2.sh
- Update assemble_docs_publish_tree.py to support v1/v2 deployment layout
- Fix mdbook preprocessor to use 'sections' key (v0.4.43 compatibility)
- Update .gitignore for new build artifact directories
- Deployment layout: / = v2 EN, /cn/ = v2 ZH, /v1/ = v1 EN, /v1/cn/ = v1 ZH

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* build: update CI to build and verify all four books (v1/v2 x EN/ZH)

- Clarify step names: "Build v2 (EN + ZH)" and "Build v1 (EN + ZH)"
- Add verification step to check all four index.html outputs exist
- Deploy workflow assembles: / = v2 EN, /cn/ = v2 ZH, /v1/ = v1 EN, /v1/cn/ = v1 ZH

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: gracefully skip missing TOC entries instead of crashing

resolve_toc_target() now returns None for missing files instead of
raising FileNotFoundError. This fixes v1 EN build where chapter index
files reference TOC entry names that don't match actual filenames.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

2026-03-12 13:37:42 +00:00

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推荐系统作为深度学习在工业界最成功的落地成果之一，极大地提升了用户的在线使用体验，并且为各大公司创造了可观的利润，从而促使各大公司持续加大对推荐系统的投入。过去两年推荐模型的规模成指数增长，带来了许多系统层面的挑战亟待解决。在实际的生产环境中面临的问题与挑战是本章区区几千字难以概括的，因此工业级推荐系统的架构必然十分复杂，本章只能抛砖引玉地简单介绍一种典型的推荐系统组成的基本架构和运行过程，并介绍了推荐系统面临的持续更新模型的挑战和一种前沿的解决方案。面对实际生产环境，具体的系统设计方案需要根据不同推荐场景的需求而变化，不存在一种万能的解决方案。

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推荐模型：Wide & Deep
消息队列介绍：什么是消息队列
特征存储介绍：什么是机器学习中的特征存储

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