The newly emerging field of Network Science deals with the tasks of modelling, comparing and summarizing large data sets that describe complex interactions. Because pairwise affin...
The aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. The pr...
In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh
For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....
In implementations of non-standard database systems, large objects are often embedded within an aggregate of different types, i.e. a tuple. For a given size and access probabilit...