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Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs
Knowledge Graphs (KGs) play a crucial role in enhancing e-commerce system performance by providing structured information about entities and their relationships, such as complementary or substitutable relations between products or product types, which can be utilized in recommender systems.
NEAT: A Label Noise-resistant Complementary Item Recommender System with Trustworthy Evaluation
On the other hand, the model evaluation will not be trustworthy if the labels for evaluation are not reflecting the true complementary relatedness.
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