Adaptive set intersections, unions, and differences
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
ACM Computing Surveys (CSUR)
ACM Computing Surveys (CSUR)
Adaptive intersection and t-threshold problems
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Region proximity in metric spaces and its use for approximate similarity search
ACM Transactions on Information Systems (TOIS)
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
A compact space decomposition for effective metric indexing
Pattern Recognition Letters
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Effective Proximity Retrieval by Ordering Permutations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approximate similarity search in metric spaces using inverted files
Proceedings of the 3rd international conference on Scalable information systems
Approximate similarity search: A multi-faceted problem
Journal of Discrete Algorithms
Indexability, concentration, and VC theory
Proceedings of the Third International Conference on SImilarity Search and APplications
Where are you heading, metric access methods?: a provocative survey
Proceedings of the Third International Conference on SImilarity Search and APplications
Succinct nearest neighbor search
Proceedings of the Fourth International Conference on SImilarity Search and APplications
Stabilizing the recall in similarity search
Proceedings of the Fourth International Conference on SImilarity Search and APplications
Scalable pattern search analysis
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
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Some metric indexes, like the pivot based family, can natively trade space for query time. Other indexes may have a small memory footprint and still outperform the pivot based approach; but are unable to increase the memory usage to boost the query time. In this paper we propose a new metric indexing technique with an algorithmic mechanism to lift the performance of otherwise rigid metric indexes. We selected the well known List of Clusters (LC) as the base data structure, obtaining an index which is orders of magnitude faster to build, with memory usage adaptable to the intrinsic dimension of the data, and faster at query time than the original LC. We also present a nearest neighbor algorithm, of independent interest, which is optimal in the sense that requires the same number of distance computations as a range query with the radius of the nearest neighbor. We present exhaustive experimental evidence supporting our claims, for both synthetic and real world datasets.