We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...
—The hidden knowledge in social networks data can be regarded as an important resource for criminal investigations which can help finding the structure and organization of a crim...
We present a framework for mining frequent trajectories, which are translated and/or rotated with respect to one another. We then discuss a multiresolution methodology, based on th...
Alexander Andreopoulos, Bill Andreopoulos, Aijun A...
Abstract. Recent times have seen an explosive growth in the availability of various kinds of data. It has resulted in an unprecedented opportunity to develop automated data-driven ...
Computational diagnosis of cancer is a classification problem, and it has two special requirements on a learning algorithm: perfect accuracy and small number of features used in t...