The UNT College of Engineering strives to educate and train engineers and technologists who have the vision to recognize and solve the problems of society. The college comprises six degree-granting departments of instruction and research.
This paper discusses integrating knowledge for subjectivity sense labeling.
Physical Description
9 p.
Notes
Abstract: This paper introduces an integrative approach to automatic word sense subjectivity annotation. We use features that exploit the hierarchical structure and domain information in lexical resources such as WordNet, as well as other types of features that measure the similarity of glosses and the overlap among sets of semantically related words. Integrated in a machine learning framework, the entire set of features is found to give better results than any individual type of feature.
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Gyamfi, Yaw; Wiebe, Janyce M.; Mihalcea, Rada, 1974- & Akkaya, Cem.Integrating Knowledge for Subjectivity Sense Labeling,
paper,
May 2009;
(https://digital.library.unt.edu/ark:/67531/metadc31013/:
accessed July 17, 2024),
University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu;
crediting UNT College of Engineering.
