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ADBIS
2007
Springer
256views Database» more  ADBIS 2007»
13 years 8 months ago
Adaptive k-Nearest-Neighbor Classification Using a Dynamic Number of Nearest Neighbors
Classification based on k-nearest neighbors (kNN classification) is one of the most widely used classification methods. The number k of nearest neighbors used for achieving a high ...
Stefanos Ougiaroglou, Alexandros Nanopoulos, Apost...
SIGMOD
1998
ACM
143views Database» more  SIGMOD 1998»
13 years 9 months ago
Optimal Multi-Step k-Nearest Neighbor Search
For an increasing number of modern database applications, efficient support of similarity search becomes an important task. Along with the complexity of the objects such as images...
Thomas Seidl, Hans-Peter Kriegel
DEXA
2003
Springer
193views Database» more  DEXA 2003»
13 years 10 months ago
Supporting KDD Applications by the k-Nearest Neighbor Join
Abstract. The similarity join has become an important database primitive to support similarity search and data mining. A similarity join combines two sets of complex objects such t...
Christian Böhm, Florian Krebs
SPIRE
2005
Springer
13 years 10 months ago
Using the k-Nearest Neighbor Graph for Proximity Searching in Metric Spaces
Proximity searching consists in retrieving from a database, objects that are close to a query. For this type of searching problem, the most general model is the metric space, where...
Rodrigo Paredes, Edgar Chávez
ICDE
2010
IEEE
295views Database» more  ICDE 2010»
13 years 11 months ago
K nearest neighbor queries and kNN-Joins in large relational databases (almost) for free
— Finding the k nearest neighbors (kNN) of a query point, or a set of query points (kNN-Join) are fundamental problems in many application domains. Many previous efforts to solve...
Bin Yao, Feifei Li, Piyush Kumar