Beyond Individuals: Modeling Mutual and Multiple Interactions for Inductive Link Prediction between Groups

计算机科学 联营 成对比较 链接(几何体) 人工智能 机器学习 群(周期表) 任务(项目管理) 图形 理论计算机科学 计算机网络 经济 有机化学 化学 管理
作者
Gongzhu Yin,Xing Wang,Hongli Zhang,Chao Meng,Yuchen Yang,Kun Lu,Yi Luo
标识
DOI:10.1145/3539597.3570448
摘要

Link prediction is a core task in graph machine learning with wide applications. However, little attention has been paid to link prediction between two group entities. This limits the application of the current approaches to many real-life problems, such as predicting collaborations between academic groups or recommending bundles of items to group users. Moreover, groups are often ephemeral or emergent, forcing the predicting model to deal with challenging inductive scenes. To fill this gap, we develop a framework composed of a GNN-based encoder and neural-based aggregating networks, namely the Mutual Multi-view Attention Networks (MMAN). First, we adopt GNN-based encoders to model multiple interactions among members and groups through propagating. Then, we develop MMAN to aggregate members' node representations into multi-view group representations and compute the final results by pooling pairwise scores between views. Specifically, several view-guided attention modules are adopted when learning multi-view group representations, thus capturing diversified member weights and multifaceted group characteristics. In this way, MMAN can further mimic the mutual and multiple interactions between groups. We conduct experiments on three datasets, including two academic group link prediction datasets and one bundle-to-group recommendation dataset. The results demonstrate that the proposed approach can achieve superior performance on both tasks compared with plain GNN-based methods and other aggregating methods.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
YL完成签到,获得积分10
1秒前
美丽的安发布了新的文献求助10
1秒前
Jasmine发布了新的文献求助30
2秒前
orixero应助科研鲁宾孙采纳,获得10
2秒前
2秒前
SaSa完成签到,获得积分10
3秒前
瘦瘦麦片发布了新的文献求助10
3秒前
honghuxian发布了新的文献求助10
3秒前
4秒前
xia完成签到,获得积分10
4秒前
5秒前
5秒前
小蘑菇应助给大佬递茶采纳,获得10
5秒前
宇哈哈发布了新的文献求助20
6秒前
量子星尘发布了新的文献求助10
6秒前
xie完成签到 ,获得积分10
7秒前
小二郎应助郗栗采纳,获得10
7秒前
Lily完成签到,获得积分10
7秒前
7秒前
7秒前
希望天下0贩的0应助陈帅采纳,获得10
8秒前
8秒前
稳重的胡萝卜完成签到,获得积分10
8秒前
CodeCraft应助张起灵采纳,获得10
9秒前
10秒前
小耗子发布了新的文献求助10
10秒前
我是老大应助嬛嬛采纳,获得10
10秒前
10秒前
11秒前
12秒前
Owen应助微风采纳,获得10
12秒前
13秒前
陈金芳完成签到,获得积分10
13秒前
傲娇如天发布了新的文献求助10
13秒前
15秒前
15秒前
跳跃的翼发布了新的文献求助10
16秒前
Ava应助可乐采纳,获得10
16秒前
一一完成签到,获得积分10
16秒前
16秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Picture Books with Same-sex Parented Families: Unintentional Censorship 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 360
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3971125
求助须知:如何正确求助?哪些是违规求助? 3515824
关于积分的说明 11179811
捐赠科研通 3250971
什么是DOI,文献DOI怎么找? 1795610
邀请新用户注册赠送积分活动 875897
科研通“疑难数据库(出版商)”最低求助积分说明 805207