Data Management Support Via Spectrum Perturbation-Based Subspace Classification in Collaborative Environments

Data management support to enable effective and efficient information sharing in collaborative environments is critical, especially in semantics based search and retrieval. In this paper, a novel spectrum perturbation-based subspace classification is proposed to mine semantics and other useful information from a large-scale dataset by utilizing a lower-dimensional subspace to discriminate different classes of the dataset. Among the existing subspace-based approaches, the Principal Component (PC) subspace is the most prevailing one and has been well studied.