<?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>余弦相似度 on 标准答案</title><link>https://www.xin800.com/tags/%E4%BD%99%E5%BC%A6%E7%9B%B8%E4%BC%BC%E5%BA%A6/</link><description>Recent content in 余弦相似度 on 标准答案</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Fri, 31 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.xin800.com/tags/%E4%BD%99%E5%BC%A6%E7%9B%B8%E4%BC%BC%E5%BA%A6/index.xml" rel="self" type="application/rss+xml"/><item><title>什么是余弦相似度</title><link>https://www.xin800.com/post/what-is-cosine-similarity/</link><pubDate>Fri, 31 Jul 2026 00:00:00 +0000</pubDate><guid>https://www.xin800.com/post/what-is-cosine-similarity/</guid><description>余弦相似度是衡量两段文本语义相似程度的打分方法，只对比方向不看长短，是文本语义匹配的首选方案。</description></item><item><title>向量接近的判断逻辑是什么</title><link>https://www.xin800.com/post/how-to-judge-vector-proximity/</link><pubDate>Fri, 31 Jul 2026 00:00:00 +0000</pubDate><guid>https://www.xin800.com/post/how-to-judge-vector-proximity/</guid><description>详解向量相似度判断的底层逻辑：向量不是逐字编码，而是整体语义的打包。通过余弦相似度衡量方向重合度。</description></item><item><title>点积与余弦相似度</title><link>https://www.xin800.com/post/dot-product-vs-cosine/</link><pubDate>Fri, 31 Jul 2026 00:00:00 +0000</pubDate><guid>https://www.xin800.com/post/dot-product-vs-cosine/</guid><description>通过Q-K点积自动算出任意两条业务信息之间关联程度，详解Thing、query-vector、key-vec等概念，区分点积与余弦相似度的本质差异。</description></item></channel></rss>