Name
Abstract | ||
|---|---|---|
The paper describes a contextual environment using the Self-Organizing Map, which can model a semantic agent (SOMAgent) that learns the correct meaning of a word used in context in order to deal with specific phenomena such as ambiguity, and to generate more precise alignments that can improve the first choice of the Statistical Machine Translation system giving linguistic knowledge. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14883-5_17 | DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE |
Field | DocType | Volume |
Computer science,Machine translation system,Machine translation,Self,Natural language processing,Artificial intelligence,Ambiguity,Machine learning | Conference | 79 |
ISSN | Citations | PageRank |
1867-5662 | 0 | 0.34 |
References | Authors | |
16 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vivian F. López Batista | 1 | 63 | 12.89 |
| Juan M. Corchado | 2 | 2899 | 239.10 |
| Juan Francisco de Paz | 3 | 395 | 52.24 |
| Sara Rodríguez | 4 | 0 | 0.34 |
| Javier Bajo | 5 | 1451 | 118.96 |