Background: Accurate and automatic gene finding and structural prediction is a common problem in bioinformatics, and applications need to be capable of handling non-canonical spli...
Alexander G. Churbanov, Mark Pauley, Daniel Quest,...
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
We propose two general and robust methods for enriching resources annotated in the Frame Semantic paradigm with syntactic dependency graphs, which can provide useful additional in...
The focus of this paper is to develop algorithms and a framework for modeling transactional data stored in relational database into graphs for mining. Most of the real-world trans...
In this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and findin...