Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark
Keywords: Recommender System, Multi-scenario Recommendation, Click-Through Rate Prediction
TL;DR: The Benchmark for Mutli-scenario Recommendation.
Abstract: Multi Scenario Recommendation (MSR) tasks, referring to building a unified model to enhance performance across all recommendation scenarios, have recently gained much attention. However, current research in MSR faces two significant challenges that hinder the field's development: the absence of uniform procedures for multi-scenario dataset processing, thus hindering fair comparisons, and most models being closed-sourced, which complicates comparisons with current SOTA models. Consequently, we introduce our benchmark, Scenario-Wise Rec, which comprises six public datasets and twelve benchmark models, along with a training and evaluation pipeline. We have also validated our benchmark using an industrial advertising dataset, further enhancing its real-world reliability. We aim for this benchmark to provide researchers with valuable insights from prior works, enabling the development of novel models based on our benchmark and thereby fostering a collaborative research ecosystem in MSR. Our source code is also available.
Primary Area: datasets and benchmarks
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Submission Number: 9690
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