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Augmenting Training Data for Massive Semantic Matching Models in Low-Traffic E-commerce Stores
We use the Aggregated Label eXtreme Multi-label Classification (AL-XMC) system (Shen et al., 2020) as an example semantic matching model and show via crowd-sourced human judgments that, when the training data is augmented through query reformulations, the quality of AL-XMC improves over a baseline that does not use query reformulation.
Efficient Online Bootstrapping for Large Scale Learning
Bootstrapping is a useful technique for estimating the uncertainty of a predictor, for example, confidence intervals for prediction.
Recommender System for Online Dating Service
Results show that collaborative filtering recommenders significantly outperform global algorithms that are currently used by dating sites.
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