# Recommender Systems and Techniques

{
  "id": "T10203",
  "title": "Recommender Systems and Techniques",
  "url": "/topics/T10203",
  "kind": "topic-directory",
  "aeo_cohort": "topic-directory",
  "provider": "openalex",
  "revision": "97e2a5b8bae626cf",
  "catalogue_revision": "f050b5d4780b1289",
  "numeric_address": "36042853512299739",
  "address_version": "morton4x16-v1",
  "coordinates": [
    3,
    17,
    1710,
    10203
  ],
  "answer_status": "Directory metadata; local answer requires separate source review",
  "truth_status": "Subject descriptor, not a factual answer or a demonstrated knowledge gap"
}

This cluster of papers focuses on the advancements in recommender system technologies, including collaborative filtering, matrix factorization, deep learning, content-based recommendation, web mining, context-aware recommender systems, neural networks, user modeling, and trust-aware recommender systems. The papers cover various techniques and methodologies for improving recommendation accuracy and addressing challenges such as cold start problems and privacy concerns.

Directory metadata is not a factual answer or evidence of a global knowledge gap.

Source: https://openalex.org/T10203

No owner-reviewed local answer yet.