Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Increasing dialogue efficiency in case-based reasoning (CBR) must be balanced against the risk of commitment to a sub-optimal solution. Focusing on incremental query elicitation i...
In order for agents and humans to leverage the growing wealth of heterogeneous information and services on the web, increasingly, they need to understand the information that is d...
Personalization actions that tailor the Web experience to a particular user are an integral component of recommender systems. Here, product knowledge - either hand-coded or “mine...
Coreference analysis, also known as record linkage or identity uncertainty, is a difficult and important problem in natural language processing, databases, citation matching and ...
This poster describes methods to enable intelligent access to multimodal information streams. We illustrate these methods in two integrated systems: the Broadcast News Editor (BNE...
FLUX belongs to the high-level programming languages for cognitive agents that have been developed in recent years. Based on the established, general action representation formali...
When a security incident occurs it is sometimes necessary to identify its causes for legal and cautionary purposes. In an attempt to hide the origin of her connection, a malicious...
To model combinatorial decision problems involving uncertainty and probability, we extend the stochastic constraint programming framework proposed in [Walsh, 2002] along a number ...