OpenTag: Open Attribute Value Extraction from Product Profiles
Table 5. OpenTag results on disjoint split; where it discovers new attribute values never seen before with 82.4% f-score.
['Train-Test Framework', 'Precision', 'Recall', 'F-score']
Discovering new attribute values with open world assumption (OWA). Therefore, we make a clear separation between training and test data such that they do not share any attribute value. Compared with the earlier random split setting, OpenTag still performs well in the disjoint setting with a f-score of 82.4% in discovering new attribute values for flavors from dog food titles. However, it is worse than random split – where it has the chance to see some attribute values during training, leading to better learning.