| Abstrakt: |
In the realm of natural language processing (NLP), Word Sense Disambiguation (WSD) is a crucial task, and WSD systems are used in many NLP applications. Systems built on WordNet (e.g., Lesk) have been witnessing encouraging progress in the domain of word sense disambiguation. Yet, the performance of WordNet based WSD systems may have limits when disambiguating polysemous words. The purpose of this research was to investigate the discrepancies between a systematic fusing approach of WordNet WSD and a single best performing system. In the experimental test, the fusing approach was used to disambiguate, and in the control test, a single best disambiguating system was used to disambiguate. The accuracies, recalls, and disambiguation times of two groups were compared after the two groups were tested by the same test dataset. The result of the experiment is that the performance accuracy and recall of the experimental group is better than that of the control group. The decision result of the multiple systems was fused to strengthen the performance accuracy and comprehensive of the system. At the disambiguation time, the experimental group showed a worthy disambiguation rate of disambiguation. [ABSTRACT FROM AUTHOR] |
