.png){kind=icon}
返回
DiffuRec: A Diffusion Model for Sequential Recommendation
.png){kind=icon}
OA
AI
DOI：10.1145/3631116.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Mainstream solutions to sequential recommendation represent items with fixed vectors. These vectors have limited capability in capturing items' latent aspects and users' diverse preferences. As a new generative paradigm, diffusion models have achieved excellent performance in areas like computer vision and natural language processing. To our understanding, its unique merit in representation generation well fits the problem setting of sequential recommendation. In this article, we make the very first attempt to adapt the diffusion model to sequential recommendation and propose DIFFUREC for item representation construction and uncertainty injection. Rather than modeling item representations as fixed vectors, we represent them as distributions in DIFFUREC, which reflect a user's multiple interests and an item's various aspects adaptively. In the diffusion phase, DIFFUREC corrupts the target item embedding into a Gaussian distribution via noise adding, which is further applied for sequential item distribution representation generation and uncertainty injection. Afterward, the item representation is fed into an approximator for target item representation reconstruction. In the reverse phase, based on a user's historical interaction behaviors, we reverse a Gaussian noise into the target item representation, then apply a rounding operation for target item prediction. Experiments over four datasets show that DIFFUREC outperforms strong baselines by a large margin.(1)
Keyword:
Diffusion model
sequential recommendation
user preference learning
期刊
IF:
9.1
论文数:
1.2K
被引数:
4.7K
机构
引用论文
.png){kind=icon}
Sensorless Control of Z Source Inverter fed BLDC Motor Drive by FOC - DTC Hybrid Control Strategy Using Fuzzy Logic Controller采用模糊逻辑控制器的foc-dtc混合控制策略的Z源逆变器馈电BLDC电机驱动的无传感器控制
PREAI
分享收藏The Signal of Solar Storms Embedded in Cosmogenic Radionuclides: Detectability and Uncertainties
OAAI
OAAI分享收藏
查看更多内容