How to reduce the search space of Entity Resolution: with Blocking or Nearest Neighbor search?

Understand

Entity Resolution suffers from quadratic time complexity.

• To increase its time efficiency, three kinds of filtering techniques are typically used for restricting its search space: (i) blocking workflows, which group together entity profiles with identical or similar signatures, (ii) string similarity join algorithms, which quickly detect entities more similar than a threshold, and (iii) nearest-neighbor methods, which convert every entity profile into a vector and quickly detect the closest entities according to the specified distance function.
• Numerous methods have been proposed for each type, but the literature lacks a comparative analysis of their relative performance.
• As we show in this work, this is a non-trivial task, due to the significant impact of configuration parameters on the performance of each filtering technique.