แนะนำงานวิจัย (AI Recommend)
ผลแนะนำสำหรับ "Graph Neural Network"
จัดอันดับความเกี่ยวข้อง
(7 รายการ)
บทความประชุมวิชาการ
100% match
ระดับนานาชาติ
GraphBERT4FakeNews: Graph-aware Bidirectional Transformer Learning for English Fake News Detection
The rapid dissemination of fake news through online news platforms and social media has become a major challenge, significantly influencing public opinion, political decision-makin...
วารสารวิชาการ
77% match
ระดับนานาชาติ (SCOPUS)
Q1
HGKAN: Hyperbolic Graph-Based Kolmogorov–Arnold Network for Social Recommendation
Social recommendation utilizes social relationships to alleviate data sparsity and improve recommendation quality. Nevertheless, existing approaches still encounter several limitat...
วารสารวิชาการ
71% match
ระดับนานาชาติ (SCOPUS)
Q1
BiTG4Rec: Bidirectional Transformer Graphs for Sequential-Social Recommendation
Sequential-social recommendation systems are essential for understanding users’ evolving interests and predicting their future behaviors. While existing methods employing bidirecti...
วารสารวิชาการ
70% match
ระดับนานาชาติ (SCOPUS)
Q1
GCA4Rec: Graph-Based Co-Attention Networks for Sequential and Social Recommendation
The integration of sequential and social recommendations using a graph-based co-attention architecture marks a significant advancement in deep learning, substantially improving rec...
วารสารวิชาการ
31% match
ระดับนานาชาติ (SCOPUS)
Q4
HGT4REC: HYPERBOLIC GRAPH TRANSFORMER FOR SEQUENTIAL AND SOCIAL RECOMMENDATION
Sequential behaviors and social ties jointly shape user preferences; however, most prior work models them in isolation and relies on shallow fusion in Euclidean space, which strugg...
วารสารวิชาการ
30% match
ระดับนานาชาติ (SCOPUS)
Q1
GCTMR: Graph Contrastive Transformer for Multibehavior Recommendation
Multibehavior recommendation aims to leverage diverse user interaction types—such as views, clicks, and purchases—to better understand user intent and enhance recommendation accura...
วารสารวิชาการ
21% match
ระดับนานาชาติ (SCOPUS)
Q3
Comparison of capability of data classification models to predict consistent results for depression
This research compares the capability of data classification models to predict consistent results for a subject’s depression potentiality, track the subject behaviour and recognise...