Abstract
Knowledge graphs have been pivotal in supporting downstream applications like search, recommendation, and question answering, among others. Therefore, knowledge graphs have naturally become key enabling technologies in e-Commerce platforms. Developing a high coverage product knowledge graph is more challenging than generic knowledge graphs. The highly specific and complex domain, the sparsity of training data, along with the dynamic taxonomies and product types, can constrain the resulting knowledge graphs. In this tutorial we present best practices and ML innovations in industry towards building a scalable product knowledge graph. Contributions in this domain benefit from the general literature in areas including information extraction and data mining, tailored to address the specific characteristics of e-Commerce platforms.
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