Iterative bootstrapping algorithms are typically compared using a single set of handpicked seeds. However, we demonstrate that performance varies greatly depending on these seeds,...
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
We present a simple algorithm for clustering semantic patterns based on distributional similarity and use cluster memberships to guide semi-supervised pattern discovery. We apply ...
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...
Distributed stream query services must simultaneously process a large number of complex, continuous queries with stringent performance requirements while utilizing distributed pro...
Sangeetha Seshadri, Bhuvan Bamba, Brian F. Cooper,...