Abstract. We consider the problem of predicting how a user will continue a given initial text fragment. Intuitively, our goal is to develop a “tab-complete” function for natura...
We present the development and tuning of a topic-adapted language model for word prediction, which improves keystroke savings over a comparable baseline. We outline our plans to d...
A statistical generative model is presented as an alternative to negative selection in anomaly detection of string data. We extend the probabilistic approach to binary classificat...
This paper describes research to enhance the integration between digital models and the services provided by the document management systems of digital libraries. Processing techn...
This paper presents a new approach to partial parsing of context-free structures. The approach is based on Markov Models. Each layer of the resulting structure is represented by i...