Date of Award
Fall 12-2014
Degree Type
Masters Thesis
Degree Name
Master of Science (MS)
Department
Computing
Committee Chair
Louise Perkins
Committee Chair Department
Computing
Committee Member 2
Sumanth Yenduri
Committee Member 2 Department
Computing
Committee Member 3
Joe Zhang
Committee Member 3 Department
Computing
Abstract
In P-bar Theory, Perkins et al. (2014) proposed a rule based method for determining the context of a partext (i.e., a part of a text document).
In Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging Brill (1995) demonstrates a method of error-driven learning applied to individual words at the sentence level to determine the part of speech each word represents.
We combine these two concepts providing a transformation-based error-driven learning algorithm to improve the results obtained from the static rules Perkins proposed and determine if the rule order prediction will provide additional metadata.
Copyright
2014, Bryant Harold Walley
Recommended Citation
Walley, Bryant Harold, "The Application of P-Bar Theory in Transformation-Based Error-Driven Learning" (2014). Master's Theses. 59.
https://aquila.usm.edu/masters_theses/59