SNCA: Semi-Supervised Node Classification for Evolving Large Attributed Graphs
Attributed graphs have an additional sign vector for each node. Typically, edge signs represent like or dislike relationship between the node pairs. This has applications in domains, such as recommender systems, personalised search, etc. However, limited availability of edge sign information in attr...
Saved in:
Main Authors: | Faima Abbasi, Muhammad Muzammal, Qiang Qu, Farhan Riaz, Jawad Ashraf |
---|---|
Format: | Article |
Language: | English |
Published: |
Tsinghua University Press
2024-09-01
|
Series: | Big Data Mining and Analytics |
Subjects: | |
Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2024.9020033 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Toward medical test recommendation from optimal attribute selection perspectives: a backward reasoning approach
by: Nengjun Zhu, et al.
Published: (2024-11-01) -
A Cloud API Personalized Recommendation Method Based on Multiple Attribute Features and Mashup Requirement Attention
by: Limin Shen, et al.
Published: (2025-01-01) -
Node Classification on The Citation Network Using Graph Neural Network
by: Irani Hoeronis, et al.
Published: (2023-06-01) -
Dual-channel attribute graph clustering beyond the homogeneity assumption
by: AN Junxiu, et al.
Published: (2025-01-01) -
Comparative analysis of Node.js frameworks
by: Bartłomiej Zima, et al.
Published: (2024-03-01)