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SIGMOD
2010
ACM

K-nearest neighbor search for fuzzy objects

10 years 2 months ago
K-nearest neighbor search for fuzzy objects
The K-Nearest Neighbor search (kNN) problem has been investigated extensively in the past due to its 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. Existing research on fuzzy objects mainly focuses on modelling basic fuzzy object types and operations, leaving the processing of more advanced queries such as kNN query untouched. In this paper, we propose two new kinds of kNN queries for fuzzy objects, Ad-hoc kNN query (AKNN) and Range kNN query (RKNN), to find the k nearest objects qualifying at a probability threshold or within a probability range. For efficient AKNN query processing, we optimize the basic best-first search algorithm by deriving more accurate approximations for the distance function between fuzzy objects and the query object. To improve the performance of RKNN search, effective pruning...
Kai Zheng, Gabriel Pui Cheong Fung, Xiaofang Zhou
Added 18 Jul 2010
Updated 18 Jul 2010
Type Conference
Year 2010
Where SIGMOD
Authors Kai Zheng, Gabriel Pui Cheong Fung, Xiaofang Zhou
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