{
  "id": 16704994,
  "title": "Do Similarity Measures Measure Similarity? How User Activity Creates Phantom Correlation in Recommender Systems",
  "url": "https://urgent.news/2026/10/26/do-similarity-measures-measure-similarity-how-user-activity-creates",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-26T17:09:56.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.35765v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Item-item similarity is one of the oldest and most foundational signals in recommender systems: two items are assumed to be similar when the same users consume them. Despite the sparsity and scale of interaction data, the implicit assumption across the field is that item co-occurrence reflects genuine shared preference, capturing what users like together. In this paper, we demonstrate that a…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}