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Previous methods of analyzing the substance of political attention have had to make several restrictive assumptions or been prohibitively costly when applied to large-scale political texts. Here, we describe a topic model for legislative speech, a statistical learning model that uses word choices to infer topical categories covered in a set of speeches and(More)
We present a novel technique for speeding up the computation of PageRank, a hyperlink-based estimate of the " importance " of Web pages, based on the ideas presented in [7]. The original PageRank algorithm uses the Power Method to compute successive iterates that converge to the principal eigenvec-tor of the Markov matrix representing the Web link graph.(More)
This paper provides a critical assessment of the Gradual Learning Algorithm (GLA) for probabilistic optimality-theoretic grammars proposed by Boersma and Hayes (2001). After a short introduction to the problem of grammar learning in OT, we discuss the limitations of the standard solution to this problem (the Constraint Demotion Algorithm by Tesar and(More)
OBJECTIVE To compare the clinical effectiveness of collaborative care with usual care in the management of patients with moderate to severe depression. DESIGN Cluster randomised controlled trial. SETTING 51 primary care practices in three primary care districts in the United Kingdom. PARTICIPANTS 581 adults aged 18 years and older who met ICD-10(More)
BACKGROUND Comprising of both organisational and patient level components, collaborative care is a potentially powerful intervention for improving depression treatment in UK primary Care. However, as previous models have been developed and evaluated in the United States, it is necessary to establish the effect of collaborative care in the UK in order to(More)