Evolutionary TBL template generation
Transformation Based Learning (TBL) is a Machine Learning technique frequently used in some Natural Language Processing (NLP) tasks. TBL uses rule templates to identify error-correcting patterns. A critical requirement in TBL is the availability of a problem domain expert to build these rule templates. In this work, we propose an evolutionary approach based on Genetic Algorithms to automatically implement the template generation process. Additionally, we report our findings on five experiments with useful NLP tasks. We observe that our approach provides template sets with a mean loss of performance of 0.5% when compared to human built templates
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Digital revista |
| Language: | English |
| Published: |
Sociedade Brasileira de Computação
2007
|
| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002007000400004 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|