Name
Title | ||
|---|---|---|
Word Sense Disambiguation And Human Intuition For Semantic Classification On Homonyms |
Abstract | ||
|---|---|---|
This paper reports a psycholinguistic research for the human intuition on the sense classification. The goal of this research is to find a computational model that fits best with our experiments on human intuition. In this regard. we compare three different computational models the Boolean model, the probabilistic model, and the probabilistic inference model. We first measured the values of each models found in the semantically annotated Sejong corpus. Then the experimental result was compared with the values in the initial measurements. Kappa statistics supports that this agreement experiment is homogeneously coincidental. The Pearson correlation coefficient test shows that the Boolean model is strongly correlated with the human intuition. |
Year | Venue | Keywords |
|---|---|---|
2006 | PACLIC 20: PROCEEDINGS OF THE 20TH PACIFIC ASIA CONFERENCE ON LANGUAGE, INFORMATION AND COMPUTATION | human intuition, homonyms, computational model, psycholinguistics, word sense disambiguation, Boolean model, probabilistic model, probabilistic inference model |
Field | DocType | Citations |
Pearson product-moment correlation coefficient,SemEval,Computer science,Boolean model,Intuition,Cohen's kappa,Computational model,Natural language processing,Artificial intelligence,Homonym,Statistical model | Conference | 0 |
PageRank | References | Authors |
0.34 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Kim | 1 | 285 | 35.51 |
| Jae-Woong Choe | 2 | 54 | 5.22 |