Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Fast algorithms for projected clustering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
SIGMOD '85 Proceedings of the 1985 ACM SIGMOD international conference on Management of data
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
Influence sets based on reverse nearest neighbor queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Four valued logic for relational database systems
ACM SIGMOD Record
Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
An Index Structure for Efficient Reverse Nearest Neighbor Queries
Proceedings of the 17th International Conference on Data Engineering
Fast High-Dimensional Data Search in Incomplete Databases
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
What Is the Nearest Neighbor in High Dimensional Spaces?
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Discovery of Influence Sets in Frequently Updated Databases
Proceedings of the 27th International Conference on Very Large Data Bases
Nearest Neighbor and Reverse Nearest Neighbor Queries for Moving Objects
IDEAS '02 Proceedings of the 2002 International Symposium on Database Engineering & Applications
Constrained Nearest Neighbor Queries
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
MIL primitives for querying a fragmented world
The VLDB Journal — The International Journal on Very Large Data Bases
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Location-based spatial queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Towards Efficient Multi-Feature Queries in Heterogeneous Environments
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
Evaluating Top-k Queries over Web-Accessible Databases
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
High dimensional reverse nearest neighbor queries
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Toward a progress indicator for database queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Reverse Nearest Neighbors in Large Graphs
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Reverse Nearest Neighbors Search in Ad-hoc Subspaces
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Reverse nearest neighbor aggregates over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Reverse kNN search in arbitrary dimensionality
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Lazy updates: an efficient technique to continuously monitoring reverse kNN
Proceedings of the VLDB Endowment
Efficient RkNN retrieval with arbitrary non-metric similarity measures
Proceedings of the VLDB Endowment
Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks
The VLDB Journal — The International Journal on Very Large Data Bases
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Given an object q, modeled by a multidimensional point, a reverse nearest neighbors (RNN) query returns the set of objects in the database that have q as their nearest neighbor. In this paper, we study an interesting generalization of the RNN query, where not all dimensions are considered, but only an ad hoc subset thereof. The rationale is that 1) the dimensionality might be too high for the result of a regular RNN query to be useful, 2) missing values may implicitly define a meaningful subspace for RNN retrieval, and 3) analysts may be interested in the query results only for a set of (ad hoc) problem dimensions (i.e., object attributes). We consider a suitable storage scheme and develop appropriate algorithms for projected RNN queries, without relying on multidimensional indexes. Given the significant cost difference between random and sequential data accesses, our algorithms are based on applying sequential accesses only on the projected atomic values of the data at each dimension, to progressively derive a set of RNN candidates. Whether these candidates are actual RNN results is then validated via an optimized refinement step. In addition, we study variants of the projected RNN problem, including RkNN search, bichromatic RNN, and RNN retrieval for the case where sequential accesses are not possible. Our methods are experimentally evaluated with real and synthetic data.