Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
In this paper we present a clustering-based method for representing semantic concepts on multimodal low-level feature spaces and study the evaluation of the goodness of such model...
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...
We present a nonparametric mode-seeking algorithm, called medoidshift, based on approximating the local gradient using a weighted estimate of medoids. Like meanshift, medoidshift ...
Query result clustering has recently attracted a lot of attention to provide users with a succinct overview of relevant results. However, little work has been done on organizing t...
Jongwuk Lee, Seung-won Hwang, Zaiqing Nie, Ji-Rong...