High-dimensional index structures database support for next decade's applications (tutorial)
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Influence sets based on reverse nearest neighbor queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
ACM Computing Surveys (CSUR)
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Querying Time Series Data Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
An Index Structure for Efficient Reverse Nearest Neighbor Queries
Proceedings of the 17th International Conference on Data Engineering
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
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Indexing the Distance: An Efficient Method to KNN Processing
Proceedings of the 27th International Conference on Very Large Data Bases
The k-Nearest Neighbour Join: Turbo Charging the KDD Process
Knowledge and Information Systems
Multiple aggregations over data streams
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
iDistance: An adaptive B+-tree based indexing method for nearest neighbor search
ACM Transactions on Database Systems (TODS)
Efficient reverse k-nearest neighbor search in arbitrary metric spaces
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Reverse Nearest Neighbor Search in Metric Spaces
IEEE Transactions on Knowledge and Data Engineering
Efficient index-based KNN join processing for high-dimensional data
Information and Software Technology
Reverse kNN search in arbitrary dimensionality
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Gorder: an efficient method for KNN join processing
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Multiple k nearest neighbor query processing in spatial network databases
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
Efficient parallel kNN joins for large data in MapReduce
Proceedings of the 15th International Conference on Extending Database Technology
Parallel k-most similar neighbor classifier for mixed data
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
A branch and bound method for min-dist location selection queries
ADC '12 Proceedings of the Twenty-Third Australasian Database Conference - Volume 124
Reverse-k-Nearest-Neighbor join processing
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
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The k Nearest Neighbor (kNN) join operation associates each data object in one data set with its k nearest neighbors from the same or a different data set. The kNN join on high-dimensional data (high-dimensional kNN join) is a very expensive operation. Existing high-dimensional kNN join algorithms were designed for static data sets and therefore cannot handle updates efficiently. In this article, we propose a novel kNN join method, named kNNJoin +, which supports efficient incremental computation of kNN join results with updates on high-dimensional data. As a by-product, our method also provides answers for the reverse kNN queries with very little overhead. We have performed an extensive experimental study. The results show the effectiveness of kNNJoin+ for processing high-dimensional kNN joins in dynamic workloads.