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Full-Text Articles in Physical Sciences and Mathematics
Exploring The Use Of Neural Transformers For Psycholinguistics, Antonio Laverghetta Jr.
Exploring The Use Of Neural Transformers For Psycholinguistics, Antonio Laverghetta Jr.
USF Tampa Graduate Theses and Dissertations
Deep learning has the potential to help solve numerous problems in cognitive science andeducation, by providing us a way to model the cognitive profiles of individual people. If this were possible, it would allow us to design targeted tests and suggest specific remediation based on each individual’s needs. On the flip side, employing techniques from psychology can give us insight into the underlying skillsets neural networks have acquired during training, addressing the interpretability concern. This thesis explores these ideas in the context of transformer language models, which have achieved state-of-the-art results on virtually every natural language processing (NLP) task. First, …
Sentiment Analysis In Peer Review, Zachariah J. Beasley
Sentiment Analysis In Peer Review, Zachariah J. Beasley
USF Tampa Graduate Theses and Dissertations
Sentiment analysis, a widely popular subfield of natural language processing, has recently been used in the classroom to predict student attrition or to determine the mood of students, teacher strengths and weaknesses, or student perception of internship experience. These are all helpful indicators for the enhancement of students' academic experience but none improve the information gathered from or the reliability of peer review. This is particularly important in large courses with complex assignments (e.g., essays, software projects, and presentations) where scalable grading is requisite. In this dissertation, we apply sentiment analysis not on an assignment itself, but on the meaningful …
Tagline: Information Extraction For Semi-Structured Text Elements In Medical Progress Notes, Dezon K. Finch
Tagline: Information Extraction For Semi-Structured Text Elements In Medical Progress Notes, Dezon K. Finch
USF Tampa Graduate Theses and Dissertations
Text analysis has become an important research activity in the Department of Veterans Affairs (VA). Statistical text mining and natural language processing have been shown to be very effective for extracting useful information from medical documents. However, neither of these techniques is effective at extracting the information stored in semi-structure text elements. A prototype system (TagLine) was developed as a method for extracting information from the semi-structured portions of text using machine learning. Features for the learning machine were suggested by prior work, as well as by examining the text, and selecting those attributes that help distinguish the various classes …