Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Assigning functions to novel proteins is one of the most important problems in the post-genomic era. Several approaches have been applied to this problem, including analyzing gene...
Minghua Deng, Kui Zhang, Shipra Mehta, Ting Chen, ...
Abstract. In the last few years, the semantics of Petri nets has been investigated in several different ways. Apart from the classical "token game", one can model the beh...
We describe a framework for characterizing people’s behavior with Digital Live Art. Our framework considers people’s wittingness, technical skill, and interpretive abilities i...
Jennifer G. Sheridan, Nick Bryan-Kinns, Alice Bayl...
In this paper, we present a novel entity coreference algorithm for Semantic Web instances. The key issues include how to locate context information and how to utilize the context ...