2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (2010)
Oct. 10, 2010 to Oct. 12, 2010
In this paper, we present our continuous research on similarity search problems. Previously we proposed PanKNNwhich 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.
similarity, K nearest neighbors, data mining, query, Fuzzy
Y. Shi and R. Rosenblum, "An Attempt to Find Neighbors," 2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery(CYBERC), Huangshan, China, 2010, pp. 318-320.