Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...
The incorporation of temporal semantic into the traditional data mining techniques has caused the creation of a new area called Temporal Data Mining. This incorporation is especial...
We investigate new approaches for frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan (graph-based Substructure pattern mining), which...
Every day, new information, products and services are being offered by providers on the World Wide Web. At the same time, the number of consumers and the diversity of their intere...
As new computer architectures are developed to exploit large-scale data-level parallelism, techniques are needed to retarget legacy sequential code to these platforms. Sequential ...