Trajectory clustering has played a crucial role in data analysis since it reveals underlying trends of moving objects. Due to their sequential nature, trajectory data are often rec...
Many real world applications such as sensor networks and other monitoring applications naturally generate probabilistic streams that are highly correlated in both time and space. ...
In recent years, the significant growth of RDF data used in numerous applications has made its efficient and scalable manipulation an important issue. In this paper, we present RD...
We address the problem of maintaining continuous skyline queries efficiently over dynamic objects with d dimensions. Skyline queries are an important new search capability for mult...
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...