With a rich variety of forms and types, digital resources are complex data objects. They grows fast in volume on the Web, but hard to be classified efficiently. The paper presents ...
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
The need of biomedical vocabularies is well known for various tasks, e.g., supporting structured data entry, decision support and electronic data exchange as well as retrieval and...