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Welcome to the Natural Language Processing Lab of the Brigham Young University Computer Science Department

If you are looking for a private wiki where lab members can coordinate on unbaked projects, please use the Private NLPWiki


Overview

Members of the Natural Language Processing lab are working on text mining problems involving the discovery of structure and patterns in large collections of documents with little or no human intervention. Projects include a topic browser based on hierarchical Bayesian topic models, error reduction in OCR of historical documents, and topic models for noisy data.

We are also working on learning to annotate lesser studied languages to aid scholarship on documents written in those languages. Approaches to solving this problem include probabilistic models of language structure and cost-conscious active learning methods. In particular, we are using these methods to facilitate the annotation of ancient documents written in Syriac, a dying Semitic language in which many significant documents of the Christian Near East were written. We are also interested in learning new and difficult tasks from both data and expert knowledge in harmonious ways using active learning, feature engineering, Bayesian models, and methods of advice-giving.

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