Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
The problem of finding locally dense components of a graph is an important primitive in data analysis, with wide-ranging applications from community mining to spam detection and ...
Abstract. Spatial Data Mining (SDM) has great potential in supporting public policy and in underpinning society functioning. One task in SDM is the discovery of characterization an...
Over the past 15 years, numerous algorithms have been proposed for frequent pattern mining as it plays an essential role in many knowledge discovery and data mining (KDD) tasks. M...
The accuracy and scalability of multiple sequence alignment (MSA) of DNAs and proteins have long been and are still important issues in bioinformatics. To rapidly construct a reas...