<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Search Engine on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/search-engine/</link><description>Recent content in Search Engine on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/search-engine/index.xml" rel="self" type="application/rss+xml"/><item><title>Hybrid Search</title><link>https://terms-en.ai-term-hub.com/en/terms/hybrid_search/</link><pubDate>Sat, 18 Jul 2026 10:01:39 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/hybrid_search/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Hybrid Search integrates two distinct retrieval methods: dense vector search, which captures semantic meaning and context, and sparse vector (keyword) search, which matches exact terms. By leveraging the strengths of both approaches, it mitigates the limitations of relying on a single method, such as missing synonyms in keyword search or lacking precision in pure semantic search. This approach is widely used in modern enterprise search engines and RAG applications to deliver highly relevant results across diverse query types.&lt;/p></description></item></channel></rss>