We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
In this paper, we present a local, adaptive optimization scheme for adjusting the number of clusters in fuzzy C-means clustering. This method is especially motivated by online app...
In this paper, we introduce a novel binary method for fast computation of an objective function to measure inter and intra class similarities, which is used for combining multiple...
Bootstrapping semantics from text is one of the greatest challenges in natural language learning. We first define a word similarity measure based on the distributional pattern of ...
Finding a set of web pages relevant to a user’s information goal is difficult due to the enormous size of the Internet. Search engines are able to find a set of pages that mat...