Progressive approximate aggregate queries with a multi-resolution tree structure
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Fast Nearest Neighbor Search in Medical Image Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
3D Similarity Search by Shape Approximation
SSD '97 Proceedings of the 5th International Symposium on Advances in Spatial Databases
Uncertainty Management for Spatial Data in Databases: Fuzzy Spatial Data Types
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Nearest and reverse nearest neighbor queries for moving objects
The VLDB Journal — The International Journal on Very Large Data Bases
ULDBs: databases with uncertainty and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Probabilistic Segmentation and Analysis of Horizontal Cells
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Dynamic skyline queries in metric spaces
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
A unified approach to ranking in probabilistic databases
Proceedings of the VLDB Endowment
K-nearest neighbor search for fuzzy objects
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Scalable Probabilistic Similarity Ranking in Uncertain Databases
IEEE Transactions on Knowledge and Data Engineering
Ranking continuous probabilistic datasets
Proceedings of the VLDB Endowment
Efficient fuzzy ranking queries in uncertain databases
Applied Intelligence
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Ranking queries have been investigated extensively in the past due to their broad range of applications. In this paper, we study this problem in the context of fuzzy objects that have indeterministic boundaries. Fuzzy objects play an important role in many areas, such as biomedical image databases and GIS. To the best of our knowledge, we present the first efficient approach for similarity ranking in fuzzy object databases. The main challenge of ranking fuzzy objects is that these objects consist of multiple instances, each associated with a probability. We propose a framework to transform fuzzy objects into probabilistic objects which can then be ranked using existing algorithms for probabilistic objects.