Comparing Simple Scoring With IRT Scoring of Personality Measures

Symbolic Preference Using Simple Scoring

Despite the popularity of stochastic parsers, symbolic parsing still has some advantages, but is not practical without an effective mechanism for selecting among alternative analyses. This paper describes the symbolic preference system of a hybrid parser that combines a shallow parser with an overlay parser that builds on the chunks. The hybrid currently equals or exceeds most stochastic parser...

Comparing Brand Personality Measures:

Comparing methods for scoring personality disorder types using maladaptive traits in DSM-5.

The DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th ed.) Section III will include an alternative hybrid system for the diagnosis of personality disorder (PD). This alternative system defines PD types partly through specific combinations of maladaptive traits, rather than by using a set of polythetic diagnostic criteria. The current report utilizes a large sample of undergradua...

Linköping: Cubic-Time Graph Parsing with a Simple Scoring Scheme

We turn the Eisner algorithm for parsing to projective dependency trees into a cubictime algorithm for parsing to a restricted class of directed graphs. To extend the algorithm into a data-driven parser, we combine it with an edge-factored feature model and online learning. We report and discuss results on the SemEval-2014 Task 8 data sets (Oepen et al., 2014).

Predicting Hospital-Acquired Infections by Scoring System with Simple Parameters

BACKGROUND Hospital-acquired infections (HAI) are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR) and validated by Artificial Neural Networks ...