The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
It is a well-known problem that intrusion detection systems overload their human operators by triggering thousands of alarms per day. As a matter of fact, we have been asked by on...
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Fluorescence microscopy is widely used to analyze the distribution of proteins within cells. As currently practiced, the assignment of a protein to a particular organelle is done ...
We describe a novel semi-supervised method called WordCodebook Learning (WCL), and apply it to the task of bionamed entity recognition (bioNER). Typical bioNER systems can be seen...