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Vendredi 12 Novembre
| Heure: |
12:30 - 13:30 |
| Lieu: |
Salle B107, bâtiment B, Université de Villetaneuse |
| Résumé: |
Relation Extraction with Distant Supervision: noise Reductio |
| Description: |
Juan Luis Garcia-Mendoza Distant Supervision is an approach that allows automatic labeling of instances. This approach has been used in Relation Extraction. Still, the main challenge of this task is handling instances with noisy labels (e.g., when two entities in a sentence are automatically labeled with an invalid relation). The approaches reported in the literature addressed this problem by employing noise-tolerant classifiers. However, if a noise reduction stage is introduced before the classification step, this increases the macro precision values or keep the same values with fewer instances. An approach based on Adversarial Autoencoders is proposed to obtain a new representation that allows noise reduction in Distant Supervision. |
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