Analyzing the impact of UMLS relations on the Word Sense Disambiguation accuracy
- Wessam Gad El-Rab
- Osmar R. Zaiane, University of Alberta (Database)
- Mohammad El-Hajj
Word-sense disambiguation (WSD) is the process of finding the correct meaning of words that have multiple meanings. The unsupervised WSD algorithm is the type of WSD algorithm that leverages an external source of knowledge to guide the disambiguation process. The unsupervised WSD algorithm type is attracting more interest in the biomedical domain because of its implementation practicality, especially when it leverages the knowledge sources of the Unified Medical Language System (UMLS), but still the resulted accuracy of the unsupervised WSD algorithm is lower than its supervised alternative. In this study we analyze the impact of using different subsets of the UMLS on the resulted accuracy of the unsupervised WSD algorithm. Our findings show that there are better ways to leverage the UMLS than using it as a monolithic source of knowledge
Citation
W. El-Rab, O. Zaiane, M. El-Hajj. "Analyzing the impact of UMLS relations on the Word Sense Disambiguation accuracy". Procedia Computer Science, 21, pp 295-301, October 2013.| Keywords: | |
| Category: | In Journal |
| Web Links: | ScienceDirect |
BibTeX
@article{El-Rab+al:13,
author = {Wessam Gad El-Rab and Osmar R. Zaiane and Mohammad El-Hajj},
title = {Analyzing the impact of UMLS relations on the Word Sense
Disambiguation accuracy},
Volume = "21",
Pages = {295-301},
journal = {Procedia Computer Science},
year = 2013,
}Last Updated: October 30, 2019Submitted by Sabina P
