Multi-task deep recommender systems: A survey
Multi-task learning (MTL) aims at learning related tasks in a unified model to achieve mutual
improvement among tasks considering their shared knowledge. It is an important topic in …
improvement among tasks considering their shared knowledge. It is an important topic in …
Single-shot feature selection for multi-task recommendations
Multi-task Recommender Systems (MTRSs) has become increasingly prevalent in a variety
of real-world applications due to their exceptional training efficiency and recommendation …
of real-world applications due to their exceptional training efficiency and recommendation …
Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
As user behaviors become complicated on business platforms, online recommendations
focus more on how to touch the core conversions, which are highly related to the interests of …
focus more on how to touch the core conversions, which are highly related to the interests of …
Residual Multi-Task Learner for Applied Ranking
Modern e-commerce platforms rely heavily on modeling diverse user feedback to provide
personalized services. Consequently, multi-task learning has become an integral part of …
personalized services. Consequently, multi-task learning has become an integral part of …
多任务推荐算法研究综述.
温民伟， 梅红岩， 袁凤源， 张晓宇… - Journal of Frontiers of …, 2024 - search.ebscohost.com
单任务推荐算法存在数据稀疏, 冷启动和推荐效果不稳定等问题. 多任务推荐算法可以将多种
类型的用户行为数据和额外信息进行联合建模, 从而更好地挖掘用户的兴趣和需求 …
类型的用户行为数据和额外信息进行联合建模, 从而更好地挖掘用户的兴趣和需求 …