Efficiently leveraging multi-level user intent for session-based recommendation via atten-mixer network
Session-based recommendation (SBR) aims to predict the user's next action based on short
and dynamic sessions. Recently, there has been an increasing interest in utilizing various …
and dynamic sessions. Recently, there has been an increasing interest in utilizing various …
Evolutionary preference learning via graph nested gru ode for session-based recommendation
Session-based recommendation (SBR) aims to predict the user's next action based on the
ongoing sessions. Recently, there has been an increasing interest in modeling the user …
ongoing sessions. Recently, there has been an increasing interest in modeling the user …
Enhanced graph neural network for session-based recommendation
Z Sheng, T Zhang, Y Zhang, S Gao - Expert Systems with Applications, 2023 - Elsevier
A key problem of session-based recommendation is to predict items of interest based on
anonymous user's current interaction session. To improve the prediction accuracy, existing …
anonymous user's current interaction session. To improve the prediction accuracy, existing …
Multi-aspect enhanced graph neural networks for recommendation
Graph neural networks (GNNs) have achieved remarkable performance in personalized
recommendation, for their powerful data representation capabilities. However, these …
recommendation, for their powerful data representation capabilities. However, these …
A survey on incremental update for neural recommender systems
P Zhang, S Kim - arXiv preprint arXiv:2303.02851, 2023 - arxiv.org
Recommender Systems (RS) aim to provide personalized suggestions of items for users
against consumer over-choice. Although extensive research has been conducted to address …
against consumer over-choice. Although extensive research has been conducted to address …
Glad-paw: Graph-based log anomaly detection by position aware weighted graph attention network
Y Wan, Y Liu, D Wang, Y Wen - … on knowledge discovery and data mining, 2021 - Springer
Anomaly detection is a crucial and challenging subject that has been studied within diverse
research areas. In this work, we focus on log data (especially computer system logs) which …
research areas. In this work, we focus on log data (especially computer system logs) which …
Modeling cross-session information with multi-interest graph neural networks for the next-item recommendation
Next-item recommendation involves predicting the next item of interest of a given user from
their past behavior. Users tend to browse and purchase various items on e-commerce …
their past behavior. Users tend to browse and purchase various items on e-commerce …
GKT-CD: Make cognitive diagnosis model enhanced by graph-based knowledge tracing
J Zhang, Y Mo, C Chen, X He - 2021 International joint …, 2021 - ieeexplore.ieee.org
Recent advancements in online education platforms have caused an increase in research
on adaptive learning system, wherein student performance on coursework exercises is …
on adaptive learning system, wherein student performance on coursework exercises is …
Multi-hop Multi-view Memory Transformer for Session-based Recommendation
AS ession-B ased R ecommendation (SBR) seeks to predict users' future item preferences
by analyzing their interactions with previously clicked items. In recent approaches, G raph N …
by analyzing their interactions with previously clicked items. In recent approaches, G raph N …
[PDF][PDF] 会话场景下基于特征增强的图神经推荐方法
黄震华， 林小龙， 孙圣力， 汤庸， 陈运文 - 计算机学报, 2022 - cjc.ict.ac.cn
摘要基于图神经网络的会话推荐(简称图神经会话推荐) 是近年来推荐系统领域的一个研究重点
和热点, 这主要是因为它们引入了会话图拓扑结构信息来提高物品和会话特征表示的准确性 …
和热点, 这主要是因为它们引入了会话图拓扑结构信息来提高物品和会话特征表示的准确性 …