We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
Today, a number of algorithms exist for constructing tag hierarchies from social tagging data. While these algorithms were designed with ontological goals in mind, we know very li...
Understanding user intent is key to designing an effective ranking system in a search engine. In the absence of any explicit knowledge of user intent, search engines want to diver...
We adopt the same mathematical model of a set M of probability measures as is central to the theory of coherent imprecise probability. However, we endow this model with an objecti...