Subspace clustering (SC) is a promising technology involving clusters that are identified
based on their association with subspaces in high-dimensional spaces. SC can be classified …

Our world and our lives are changing in many ways. Communication, networking, and
computing technologies are among the most influential enablers that shape our lives today …

The kNN join problem, denoted by R× KNN S, is to find the k nearest neighbors from a given
dataset S for each point in the query set R. It is an operation required by many big data …

Ambient Intelligence (AmI) is a muldisciplinary area which refers to environments that are
sensitive and responsive to the presence of people and objects. The rapid progress of …

Principal component analysis (PCA) is an important tool in many areas including data
reduction and interpretation, information retrieval, image processing, and so on. Kernel PCA …

Clustering is the basic composition of data analysis, which also plays a significant role in
microarray analysis. Gaussian mixture model (GMM) based clustering is very popular …

Nearest neighbor retrieval is the task of identifying, given a database of objects and a query
object, the objects in the database that are the most similar to the query. Retrieving nearest …