scholarly journals An efficient k nearest neighbor search for multivariate time series

2007 ◽  
Vol 205 (1) ◽  
pp. 65-98 ◽  
Author(s):  
Kiyoung Yang ◽  
Cyrus Shahabi
Keyword(s):  
Time Series ◽  
Nearest Neighbor ◽  
Multivariate Time Series ◽  
Nearest Neighbor Search ◽  
K Nearest Neighbor ◽  
Neighbor Search ◽  
K Nearest Neighbor Search

scholarly journals Two-Pass K Nearest Neighbor Search for Feature Tracking

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 72939-72951
Author(s):  
Mingwei Cao ◽  
Wei Jia ◽  
Zhihan Lv ◽  
Wenjun Xie ◽  
Liping Zheng ◽  
...  
Keyword(s):  
Feature Tracking ◽  
Nearest Neighbor ◽  
Nearest Neighbor Search ◽  
K Nearest Neighbor ◽  
Neighbor Search ◽  
K Nearest Neighbor Search

scholarly journals k-Nearest Neighbor Search based on Node Density in MANETs

2014 ◽  
Vol 10 (4) ◽  
pp. 385-405 ◽  
Author(s):  
Yuka Komai ◽  
Yuya Sasaki ◽  
Takahiro Hara ◽  
Shojiro Nishio
Keyword(s):  
Query Processing ◽  
Nearest Neighbor ◽  
Nearest Neighbor Search ◽  
K Nearest Neighbor ◽  
Node Density ◽  
Neighbor Search ◽  
Query Result ◽  
Knn Query ◽  
The One ◽  
K Nearest Neighbor Search

In a kNN query processing method, it is important to appropriately estimate the range that includes kNNs. While the range could be estimated based on the node density in the entire network, it is not always appropriate because the density of nodes in the network is not uniform. In this paper, we propose two kNN query processing methods in MANETs where the density of nodes is ununiform; the One-Hop (OH) method and the Query Log (QL) method. In the OH method, the nearest node from the point specified by the query acquires its neighbors' location and then determines the size of a circle region (the estimated kNN circle) which includes kNNs with high probability. In the QL method, a node which relays a reply of a kNN query stores the information on the query result for future queries.

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