Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large sets of documents into a small number of meaningful ...
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
Previous works on automatic query clustering most generate a flat, un-nested partition of query terms. In this work, we are pursuing to organize query terms into a hierarchical s...
In this work, we investigate the use of online or “crawling” algorithms to sample large social networks in order to determine the most influential or important individuals wit...