Association Rules Mining for Name Entity Recognition
| dc.contributor.author | Indra Budi | en_US |
| dc.contributor.author | Stephane Bressan | en_US |
| dc.date.accessioned | 2004-10-21T14:28:52Z | en_US |
| dc.date.accessioned | 2017-01-23T06:59:40Z | |
| dc.date.available | 2004-10-21T14:28:52Z | en_US |
| dc.date.available | 2017-01-23T06:59:40Z | |
| dc.date.issued | 2003-06-01T00:00:00Z | en_US |
| dc.description.abstract | We propose a new name entity class recognition method based on association rules. We evaluate and compare the performance of our method with the state of the art maximum entropy method. We show that our method consistently yields a higher precision at a competitive level of recall. This result makes our method particularly suitable for tasks whose requirements emphasize the quality rather than the quantity of results. | en_US |
| dc.format.extent | 315327 bytes | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.uri | https://dl.comp.nus.edu.sg/xmlui/handle/1900.100/1413 | en_US |
| dc.language.iso | en | en_US |
| dc.relation.ispartofseries | TRA6/03 | en_US |
| dc.title | Association Rules Mining for Name Entity Recognition | en_US |
| dc.type | Technical Report | en_US |