Jeong Choi

FPAdaMetric: False-Positive-Aware Adaptive Metric Learning for Session-Based Recommendation

Modern recommendation systems are mostly based on implicit feedback data which can be quite noisy due to false positives (FPs) caused by many reasons, such as misclicks or quick curiosity. Numerous recommendation algorithms based on collaborative filtering have leveraged post-click user behavior (e.…