Sensor networks have the potential to empower domain experts from a wide range of fields. However, presently they are notoriously difficult for these domain experts to program, ...
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
The current work applies Conditional Random Fields to the problem of temporal reference mapping from Chinese text to English text. The learning algorithm utilizes a moderate number...
Abstract. We aim to create a model of emotional reactive virtual humans. This model will help to define realistic behavior for virtual characters based on emotions and events in t...