Median-shift is a mode seeking algorithm that relies on
computing the median of local neighborhoods, instead of
the mean. We further combine median-shift with Locality
Sensitive...
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Recently, the analysis of moving objects has become one of the most important technologies to be used in various applications such as GIS, navigation systems, and locationbased in...
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...