<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>图检索 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E5%9B%BE%E6%A3%80%E7%B4%A2/</link><description>Recent content in 图检索 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Sun, 12 Jul 2026 21:30:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E5%9B%BE%E6%A3%80%E7%B4%A2/index.xml" rel="self" type="application/rss+xml"/><item><title>知识图谱增强的RAG系统实践</title><link>https://guijiagi.com/posts/article-28/</link><pubDate>Sun, 12 Jul 2026 21:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-28/</guid><description>将知识图谱引入RAG系统，解决传统向量检索的语义鸿沟与多跳推理难题</description></item><item><title>知识图谱增强的RAG系统实践</title><link>https://guijiagi.com/posts/b2-55210222/</link><pubDate>Sun, 12 Jul 2026 21:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-55210222/</guid><description>将知识图谱引入RAG系统，解决传统向量检索的语义鸿沟与多跳推理难题</description></item><item><title>混合RAG：图+向量检索的协同威力</title><link>https://guijiagi.com/posts/hybrid-rag-graph-vector/</link><pubDate>Thu, 02 Jul 2026 10:36:00 +0800</pubDate><guid>https://guijiagi.com/posts/hybrid-rag-graph-vector/</guid><description>深入探讨图检索与向量检索的混合架构，发挥结构化与非结构化检索的协同优势</description></item><item><title>GraphRAG图检索增强生成</title><link>https://guijiagi.com/posts/graphrag-graph-retrieval/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/graphrag-graph-retrieval/</guid><description>GraphRAG图检索增强生成</description></item><item><title>GraphRAG图检索增强生成</title><link>https://guijiagi.com/posts/graphrag-knowledge-graph-rag/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/graphrag-knowledge-graph-rag/</guid><description>GraphRAG图检索增强生成的原理、架构与实践，突破传统向量检索的局限性</description></item></channel></rss>