Branch Mathematics and Statistics Faculty and Staff Publications
Document Type
Article
Publication Date
2019
Abstract
In this paper, a special type of polysemantic words, that is, words with multiple meanings for the same part of speech, are analyzed under the name of neutrosophic words. These words represent the most difficult cases for the disambiguation algorithms as they represent the most ambiguous natural language utterances. For approximate their meanings, we developed a semantic representation framework made by means of concepts from neutrosophic theory and entropy measure in which we incorporate sense related data. We show the advantages of the proposed framework in a sentiment classification task.
Publication Title
IEEE Access
Language (ISO)
English
Keywords
Neutrosophic sets, semantic word representation, sentiment classification
Recommended Citation
Colhon, Mihaela; Florentin Smarandache; and Dan Valeriu Voinea. "Entropy of Polysemantic Words for the Same Part of Speech." IEEE Access (2019). https://digitalrepository.unm.edu/math_fsp/583
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
