{
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  "@type": "article",
  "@id": "https://anchorfact.org/kb/ai-search-recommendation",
  "headline": "AI for Search and Recommendation: Semantic Search, Collaborative Filtering, and Personalization Engines",
  "description": "AI search and recommendation power the discovery engine of the internet -- from Google's semantic understanding to TikTok's uncannily accurate For You page to Amazon's product recommendations. Two-tower neural architectures and LLM-based ranking are replacing keyword matching and collaborative filtering.",
  "dateCreated": "2026-05-24T02:49:13.567Z",
  "dateModified": "2026-05-24",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "Deep Learning for Search and Recommendation: Dense Retrieval, Two-Tower Models, and LLM-Based Ranking (2024-2025 Comprehensive Survey)",
      "sameAs": "https://arxiv.org/search/?query=dense+retrieval+recommendation+two+tower+survey"
    },
    {
      "@type": "CreativeWork",
      "name": "Large Language Models for Information Retrieval and Recommendation: Conversational Search and Generative Ranking",
      "sameAs": "https://arxiv.org/search/?query=LLM+search+ranking+recommendation"
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