Beyond Globally Optimal: Focused Learning for Improved Recommendations

    WWW, pp. 203-212, 2017.

    Cited by: 14|Bibtex|Views17|Links
    EI

    Abstract:

    When building a recommender system, how can we ensure that all items are modeled well? Classically, recommender systems are built, optimized, and tuned to improve a global prediction objective, such as root mean squared error. However, as we demonstrate, these recommender systems often leave many items badly-modeled and thus under-served....More

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