论文标题
TAOBAO搜索中的多目标个性化产品检索
Multi-Objective Personalized Product Retrieval in Taobao Search
论文作者
论文摘要
在淘宝（Tamobao）等大型电子商务平台中，检索满足数十亿候选人的用户的产品是一个巨大的挑战。这是学术界和工业的普遍关注点。最近，通过增强基于嵌入的检索（EBR）方法，包括在TAOBAO搜索引擎中使用基于嵌入的检索（EBR）方法[16]，已通过增强基于嵌入的检索（EBR）方法来取得重大改进。但是，我们发现MGDSPR与我们的在线系统中的其他检索方法（例如词汇匹配和协作过滤）相比，相关性和个性化较弱仍然存在问题。这些问题促进了我们在相关估计和个性化检索中进一步增强EBR模型的能力。在本文中，我们提出了一种具有四个层次优化目标的新型多目标个性化产品检索（MOPPR）模型：相关性，曝光，点击和购买。我们构建了整个空间多阳性样品来训练MOPPR，而不是现有EBR模型的单阳性样品。我们采用修改后的软磁损耗来优化多个目标。广泛的离线和在线实验的结果表明，MOPPR在相关性估计和个性化检索的评估指标上优于基线MGDSPR。在28天的在线A/B测试中，MOPPR可实现0.96％的交易和1.29％的GMV提高。自2021年Double-11购物节以来，MOPPR已全面部署在移动淘宝搜索中，取代了以前的MGDSPR。最后，我们讨论了有关多目标检索和排名为社区做出贡献的一些更深入的探索的高级主题。
In large-scale e-commerce platforms like Taobao, it is a big challenge to retrieve products that satisfy users from billions of candidates. This has been a common concern of academia and industry. Recently, plenty of works in this domain have achieved significant improvements by enhancing embedding-based retrieval (EBR) methods, including the Multi-Grained Deep Semantic Product Retrieval (MGDSPR) model [16] in Taobao search engine. However, we find that MGDSPR still has problems of poor relevance and weak personalization compared to other retrieval methods in our online system, such as lexical matching and collaborative filtering. These problems promote us to further strengthen the capabilities of our EBR model in both relevance estimation and personalized retrieval. In this paper, we propose a novel Multi-Objective Personalized Product Retrieval (MOPPR) model with four hierarchical optimization objectives: relevance, exposure, click and purchase. We construct entire-space multi-positive samples to train MOPPR, rather than the single-positive samples for existing EBR models.We adopt a modified softmax loss for optimizing multiple objectives. Results of extensive offline and online experiments show that MOPPR outperforms the baseline MGDSPR on evaluation metrics of relevance estimation and personalized retrieval. MOPPR achieves 0.96% transaction and 1.29% GMV improvements in a 28-day online A/B test. Since the Double-11 shopping festival of 2021, MOPPR has been fully deployed in mobile Taobao search, replacing the previous MGDSPR. Finally, we discuss several advanced topics of our deeper explorations on multi-objective retrieval and ranking to contribute to the community.
