Abstract-Similarity searching often reduces to finding the k nearest neighbors to a query object. Finding the k nearest neighbors is achieved by applying either a depth-first or a ...
Similarity retrieval mechanisms should utilize generalized quadratic form distance functions as well as the Euclidean distance function since ellipsoid queries parameters may vary...
The Self-Organizing map (SOM), a powerful method for data mining and cluster extraction, is very useful for processing data of high dimensionality and complexity. Visualization met...
The k-means algorithm is widely used for clustering, compressing, and summarizing vector data. In this paper, we propose a new acceleration for exact k-means that gives the same a...
Multimedia similarity search has been playing a critical role in many novel applications. Typically, multimedia objects are described by high-dimensional feature vectors (or point...
Zi Huang, Heng Tao Shen, Jiajun Liu, Xiaofang Zhou