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Recall

Recall

Jun 06, 20261 min read

  • evaluation
  • key-formula

Recall

Recall

Recall=∣relevant∣∣relevant∩retrieved∣​

Fraction of relevant documents that are retrieved.

High recall = few false negatives. Trade-off with Precision — improving one typically hurts the other.

Appears In

  • IR-L04 - Evaluation
  • RS-L01 - Course Overview & Introduction
  • RS-L02 - Evaluation Beyond Accuracy
  • RS-L04 - Generative Recommendation

Graph View

  • Recall
  • Appears In

Backlinks

  • B Testing
  • Beyond-Accuracy Metrics
  • Catalog Coverage
  • Collaborative Filtering
  • Content-Based Recommendation
  • Cranfield Paradigm
  • Diversity
  • F-Measure
  • GRU4Rec
  • Hit Rate
  • Implicit and Explicit Feedback
  • LLM-based Recommendation
  • Listwise LTR
  • Matrix Factorization
  • Maximal Marginal Relevance (MMR)
  • Neighborhood-based Collaborative Filtering
  • Next-Item Prediction
  • Novelty
  • Online and Offline Evaluation
  • Pooling
  • Precision
  • Recommender System
  • SASRec
  • Serendipity
  • Session-based Recommendation
  • Top-N Recommendation
  • IR-PTR Ch2 - Setting the Stage
  • IR-A01 - Unsupervised Retrieval
  • IR - Overview
  • IR-L04 - Evaluation
  • RS-L01 - Course Overview & Introduction
  • RS-L02 - Evaluation Beyond Accuracy
  • RecSys - Overview

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