基于元学习的多视图对比融合冷启动推荐算法  

Multi-view contrast fusion cold start recommendation algorithm based on meta-learning

作　　者：张子扬 刘小洋[1] Zhang Ziyang;Liu Xiaoyang(School of Computer Science&Engineering,Chongqing University of Technology,Chongqing 400054,China)

机构地区：[1]重庆理工大学计算机科学与工程学院,重庆400054

出　　处：《计算机应用研究》2024年第7期2025-2032,共8页Application Research of Computers

基　　金：重庆市社科联重点项目(2023NDZD09);重庆市教委人文社科重点项目(23SKGH247)。

摘　　要：针对当前冷启动推荐模型在处理异质信息网络时难以充分挖掘结构与语义信息,以及忽略网络中用户行为属性的问题,提出了一种基于元学习的多视图对比融合冷启动推荐算法(MVC-ML)。该算法在模型层和数据层双重作用下,有效缓解了冷启动问题。在MVC-ML算法框架中,首先通过元路径视图提取异质信息网络的高阶语义信息;其次,利用网络模式视图捕获网络的结构特征;再接着,通过聚类视图分析用户行为属性信息;最后,运用对比学习方法,将上述三个视图中提炼的信息进行综合融合,以生成准确的表示向量。通过在DBook等三个数据集上的实验验证,MVC-ML模型在冷启动场景下相较MetaHIN等传统异质信息网络模型,在MAE上降低了1.67%,在RMSE上降低了2.06%,同时nDCG@K提高了1.48%。这些数据充分证实了MVC-ML算法的合理性和有效性。Addressing the challenges faced by current cold start recommendation models in effectively mining structural and semantic information in heterogeneous information networks,and their tendency to overlook user behavior attributes within these networks,this paper introduced a meta-learning-based multi-view contrast fusion cold start recommendation algorithm(MVC-ML).This algorithm effectively tackled the cold start problem at both the model and data layers.Within the MVC-ML framework,it firstly extracted higher-order semantic information from heterogeneous information networks using a meta-path view.Subsequently,it captured the network’s structural features using a network pattern view.Following this,the algorithm analyzed user behavior attribute information through a clustering view.Finally,MVC-ML employed a contrast learning method to integrate the information extracted from these three views,thus generating accurate representation vectors.Experimental validations on datasets,including DBook,demonstrate that the MVC-ML model,in a cold start scenario,reduces MAE by 1.67%,lowers RMSE by 2.06%,and increases nDCG@K by 1.48%compared to traditional heterogeneous information network models such as MetaHIN.These results fully confirm the rationality and effectiveness of the MVC-ML algorithm.

关 键 词：异质信息网络 对比学习 网络模式 冷启动 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]