Fast and Exact Nearest Neighbor Search in Hamming Space on Full-Text Search Engines

Understand

A growing interest has been witnessed recently from both academia and industry in building nearest neighbor search (NNS) solutions on top of full-text search engines.

• Compared with other NNS systems, such solutions are capable of effectively reducing main memory consumption, coherently supporting multi-model search and being immediately ready for production deployment.
• In this paper, we continue the journey to explore specifically how to empower full-text search engines with fast and exact NNS in Hamming space (i.e., the set of binary codes).
• By revisiting three techniques (bit operation, subs-code filtering and data preprocessing with permutation) in information retrieval literature, we develop a novel engineering solution for full-text search engines to efficiently accomplish this special but important NNS task.