Comparative Analysis of Data Structures for Approximate Nearest Neighbor Search

By Alexander Ponomarenko, N. Avrelin, Bilegsaikhan Naidan, Leonid Boytsov. 2014

26 citations recorded by the source corpus.

Subfields: Information Retrieval & Search, Algorithms & Complexity

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Retrieval & Search

1. Alexander Ponomarenko
2. Bilegsaikhan Naidan
3. Leonid Boytsov
4. Tom Drummond
5. Ben Harwood
6. Eric Nyberg

In Algorithms & Complexity

1. Alexander Ponomarenko
2. Eric Nyberg
3. Tom Drummond
4. Bilegsaikhan Naidan
5. Leonid Boytsov

Citations in the corpus

• Permutation Search Methods are Efficient, Yet Faster Search is Possible (2015, result): “The results of the preliminary evaluation were published elsewhere [32].”
• Query-Based Improvement Procedure and Self-Adaptive Graph Construction Algorithm for Approximate Nearest Neighbor Search (2015, methodology): “Also a good overview of methods for the exact nearest neighbor search can be found in [1] and an empirical comparison of several approximate state of the art methods can be found in [3].”
• FANNG: Fast Approximate Nearest Neighbour Graphs (2016, background): “…e(Pi, Pj) sorted by distance(Pi, Pj) 5 for each edge ej do 6 u← index of end vertex of ej 7 L← length of ej 8 occluded← false 9 for each edge Ek with start vertex Pi do 10 v ← index of end vertex of Ek 11 if distance(Pu, Pv) < L then 12 occluded← true 13 if not occluded then 14 add edge ej to E”