Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
The ability to accurately judge the similarity between natural language sentences is critical to the performance of several applications such as text mining, question answering, an...
Discovering accurate and interesting classification rules is a significant task in the post-processing stage of a data mining (DM) process. Therefore, an optimization problem exis...
Median averaging is a powerful averaging concept on sets of vector data in finite dimensions. A generalization of the median for shapes in the plane is introduced. The underlying ...
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...