Abstract
This article reviews index structures for fast similarity search for objects represented by binary vectors (with components equal to 0 or 1). Structures for both exact and approximate search by Hamming distance and other similarity measures are considered. Mainly, index structures are presented that are based on hash tables and similarity-preserving hashing and also on tree structures, neighborhood graphs, and distributed neural autoassociative memory. Ideas of well-known algorithms and algorithms proposed in recent years are stated.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
