Philip Bramsen

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Sociolinguists have long argued that social context influences language use in all manner of ways, resulting in lects 1 . This paper explores a text classification problem we will call lect modeling, an example of what has been termed computational sociolinguistics. In particular, we use machine learning techniques to identify social power relationships(More)
A method for automatic analysis of time-oriented clinical narratives would be of significant practical import for medical decision making, data modeling and biomedical research. This paper proposes a robust corpus-based approach for temporal analysis of medical discharge summaries. We characterize temporal organization of clinical narratives in terms of(More)
We consider the problem of constructing a directed acyclic graph that encodes temporal relations found in a text. The unit of our analysis is a temporal segment, a fragment of text that maintains temporal coherence. The strength of our approach lies in its ability to simultaneously optimize pairwise ordering preferences and global constraints on the graph(More)
This thesis focuses on developing decoding techniques for complex Natural Language Processing (NLP) tasks. The goal of decoding is to find an optimal or near optimal solution given a model that defines the goodness of a candidate. The task is challenging because in a typical problem the search space is large, and the dependencies between elements of the(More)
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