Mis on ANN-otsing ja kuidas see erineb täpse KNN-st?

ANN (Approximate Nearest Neighbor) search is a method for finding nearest neighbors that returns approximate results much faster compared to exact KNN (K-Nearest Neighbors).

Differences:

• Accuracy: Exact KNN guarantees finding exactly K nearest neighbors, while ANN may return neighbors that are close but not necessarily the closest.
• Speed: ANN is significantly faster, especially on large and high-dimensional data, using heuristics and index structures (e.g., trees, hashing).
• Application: ANN is widely used in recommendation systems, in searches within vector databases, where speed and scalability are important.

Example: when searching for similar images in a database of millions of vectors, ANN can quickly find similar matches, although not always perfectly accurate, whereas exact KNN would be too slow.