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Toward Understanding Privileged Features Distillation in Learning-to-Rank
Such features naturally arise in merchandised recommendation systems; for instance, "user clicked this item" as a feature is predictive of "user purchased this item" in the offline data, but is clearly not available during online serving.
PLAtE: A Large-scale Dataset for List Page Web Extraction
Recently, neural models have been leveraged to significantly improve the performance of information extraction from semi-structured websites.
Analysis of E-commerce Ranking Signals via Signal Temporal Logic
The timed position of documents retrieved by learning to rank models can be seen as signals.
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