Computing the pairwise semantic similarity between all words on the Web is a computationally challenging task. Parallelization and optimizations are necessary. We propose a highly...
Patrick Pantel, Eric Crestan, Arkady Borkovsky, An...
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
Many Knowledge workers are increasingly using online resources to find out latest developments in their specialty and articles of interest. To extract relevant information from s...
A problem of supervised approaches for text classification is that they commonly require high-quality training data to construct an accurate classifier. Unfortunately, in many real...
Many searches on the web have a transactional intent. We argue that pages satisfying transactional needs can be distinguished from the more common pages that have some information...