Utility-Oriented Reranking with Counterfactual Context
Yunjia Xi,
Weiwen Liu,
Xinyi Dai
et al.
Abstract:As a critical task for large-scale commercial recommender systems, reranking rearranges items in the initial ranking lists from the previous ranking stage to better meet users’ demands. Foundational work in reranking has shown the potential of improving recommendation results by uncovering mutual influence among items. However, rather than considering the context of initial lists as most existing methods do, an ideal reranking algorithm should consider the
counterfactual context
– the p… Show more
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