Identifying Controversial Pairs in Item-to-Item Recommendations

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Recommendation systems in large-scale online marketplaces are essential to aiding users in discovering new content. However, state-of-the-art systems for item-to-item recommendation tasks are often based on a shallow level of contextual relevance, which can make the system insufficient for tasks where item relationships are more nuanced. Contextually relevant item pairs can sometimes have problematic relationships that are confusing or even controversial to end users, and they could degrade user experiences and brand perception when recommended to users. For example, the…