Vorono trees and clustering problems
Information Systems
Data structures and algorithms for nearest neighbor search in general metric spaces
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
Some approaches to best-match file searching
Communications of the ACM
ACM Computing Surveys (CSUR)
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
Near Neighbor Search in Large Metric Spaces
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Searching in metric spaces by spatial approximation
The VLDB Journal — The International Journal on Very Large Data Bases
Index-driven similarity search in metric spaces (Survey Article)
ACM Transactions on Database Systems (TODS)
Similarity Search in Multimedia Databases
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Dynamic spatial approximation trees
Journal of Experimental Algorithmics (JEA)
SISAP '08 Proceedings of the First International Workshop on Similarity Search and Applications (sisap 2008)
Dynamic Spatial Approximation Trees for Massive Data
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
Enlarging nodes to improve dynamic spatial approximation trees
Proceedings of the Third International Conference on SImilarity Search and APplications
Fully dynamic metric access methods based on hyperplane partitioning
Information Systems
An access structure for similarity search in metric spaces
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
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Metric space searching is an emerging technique to address the problem of efficient similarity searching in many applications, including multimedia databases and other repositories handling complex objects. Although promising, the metric space approach is still immature in several aspects that are well established in traditional databases. In particular, most indexing schemes are not dynamic. From the few dynamic indexes, even fewer work well in secondary memory. That is, most of them need the index in main memory in order to operate efficiently. In this paper we introduce two different secondary-memory versions of the Dynamic Spatial Approximation Tree with Clusters (DSACL-tree from Barroso et al.) which has shown to be competitive in main memory. These two indexes handle well the secondary memory scenario and are competitive with the state of the art. But in particular the innovations proposed by the version DSACL+-tree lead to significant performance improvements.The resulting data structures can be useful in a wide range of database application.