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Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data
[article]
2020
arXiv
pre-print
Product catalogs are valuable resources for eCommerce website. In the catalog, a product is associated with multiple attributes whose values are short texts, such as product name, brand, functionality and flavor. Usually individual retailers self-report these key values, and thus the catalog information unavoidably contains noisy facts. Although existing deep neural network models have shown success in conducting cross-checking between two pieces of texts, their success has to be dependent upon
arXiv:2006.08779v3
fatcat:s37nllkjhvabfie76ribxyv7mu