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2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (2010)
Huangshan, China
Oct. 10, 2010 to Oct. 12, 2010
ISBN: 978-0-7695-4235-5
pp: 318-320
ABSTRACT
In this paper, we present our continuous research on similarity search problems. Previously we proposed PanKNN[18]which is a novel technique that explores the meaning of K nearest neighbors from a new perspective, redefines the distances between data points and a given query point Q, and efficiently and effectively selects data points which are closest to Q. It can be applied in various data mining fields. In this paper, we present our approach to solving the similarity search problem in the presence of obstacles. We apply the concept of obstacle points and process the similarity search problems in a different way. This approach can assist to improve the performance of existing data analysis approaches.
INDEX TERMS
similarity, K nearest neighbors, data mining, query, Fuzzy
CITATION
Yong Shi, Ryan Rosenblum, "An Attempt to Find Neighbors", 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, vol. 00, no. , pp. 318-320, 2010, doi:10.1109/CyberC.2010.64
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