We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
Abstract Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organiza...
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
A comparison of several approaches that use graph matching and cascade filtering for landmark localisation in 3D face data is presented. For the first method, we apply the structur...