• 1 Entity Resolution: Past, Present, and Yet-to-Come
  • 2 Preliminaries
    • 2.1 Computational Cost
    • 2.2 Performance Evaluation
  • 3 Generation 1: Addressing Veracity
    • 3.1 Schema Alignment
    • 3.2 Blocking
      • 3.2.1 Local Blocking Methods
      • 3.2.2 Global Blocking Methods
      • 3.2.3 Hybrid Methods
      • 3.2.4 Discussion
    • 3.3 Matching
      • 3.3.1 Distance-Based Methods
      • 3.3.2 Probabilistic Methods
      • 3.3.3 Supervised Methods
      • 3.3.4 Active Learning Methods
      • 3.3.5 Unsupervised Methods
      • 3.3.6 Collective Methods
      • 3.3.7 Rule-Based Methods
      • 3.3.8 String Similarity Joins
    • 3.4 Clustering
  • 4 Generation 2: Also Addressing Volume
    • 4.1 Blocking
    • 4.2 Matching
    • 4.3 Clustering
  • 5 Generation 3: Also Addressing Variety
    • 5.1 Schema Refinement
    • 5.2 Block Building
    • 5.3 Block Processing
    • 5.4 Matching
      • 5.4.1 Context-Based Matching
      • 5.4.2 Context-Free Matching
    • 5.5 Clustering
    • 5.6 Parallelization
      • 5.6.1 Block Building
      • 5.6.2 Block Processing
      • 5.6.3 Matching
      • 5.6.4 Clustering
  • 6 Generation 4: Also Addressing Velocity
    • 6.1 Progressive Entity Resolution
      • 6.1.1 Prioritization
    • 6.2 Incremental Entity Resolution
  • 7 Leveraging External Knowledge
    • 7.1 Deep Learning
      • 7.1.1 Schema Matching
      • 7.1.2 Blocking
      • 7.1.3 Matching
    • 7.2 Crowdsourced Entity Resolution
  • 8 Resources for Entity Resolution
    • 8.1 ER Tools
    • 8.2 ER Datasets
  • 9 Possible Directions for Future Work
  • Bibliography
  • Authors’ Biographies