An Efficient Searching Algorithm for Approximate Nearest Neighbor Queries in High Dimensions

Authors:
Sakti Pramanik;Scott Alexander;Jinhua Li
Affiliations:
-;-;-
Venue:
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Year:
1999

Citing 0
Cited 4

An Efficient Incremental Lower Bound Approach for Solving Approximate Nearest-Neighbor Problem of Complex Vague Queries

FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
Region proximity in metric spaces and its use for approximate similarity search

ACM Transactions on Information Systems (TOIS)
Approximate similarity search in metric spaces using inverted files

Proceedings of the 3rd international conference on Scalable information systems
An approach to content-based image retrieval based on the Lucene search engine library

ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present an approximate nearest neighbor search algorithm that use heuristics to decide whether or not to access a node in the index tree based on three interesting data distribution properties. We demonstrate that the proposed algorithm significantly reduces the number of nodes accessed over the algorithms that have been proposed in earlier works. Also, it will be demonstrated in this paper that the proposed algorithm can retain close to 100% of the K nearest neighbors in most cases.