4 papers with code • 0 benchmarks • 0 datasets
We annotate a multimodal product attribute value dataset that contains 87, 194 instances, and the experimental results on this dataset demonstrate that explicitly modeling the relationship between attributes and values facilitates our method to establish the correspondence between them, and selectively utilizing visual product information is necessary for the task.
Supplementing product information by extracting attribute values from title is a crucial task in e-Commerce domain.
We study this problem in the context of product catalogs that often have missing values for many attributes of interest.
Effectively filtering out noisy articles as well as bad answers is the key to improving extraction accuracy.