科言猫
学术研究的AI总结
首页
文献互助
订阅
我的收藏
科研工具
选题分析
论文总结
专利管理
未登录
返回
V
Van-Doan Nguyen
La Trobe University
10
H指数
31
论文数
356
被引数
0
相关解读
订阅
收录论文
7
发表时间
发表时间
IF
被引数
A Comprehensive Study of Anomaly Detection Schemes in IoT Networks Using Machine Learning Algorithms
基于机器学习算法的物联网网络异常检测方案综合研究
SENSORS
IF
3.5
2021-12-13
50
OA
AI
Diro, Abebe; Chilamkurti, Naveen; Nguyen, Van-Doan; Heyne, Will
分享
收藏
Integrating Community Context Information Into a Reliably Weighted Collaborative Filtering System Using Soft Ratings
ieee transactions on cybernetics
IF
8.7
2020-04-01
11
PRE
AI
Van-Doan Nguyen; Van-Nam Huynh; Sriboonchilta, Songsak
分享
收藏
Application of materials informatics on crystalline materials for two-body terms approximation
材料信息学在晶体材料二体项近似中的应用
COMPUTATIONAL MATERIALS SCIENCE
IF
3.3
2019-08-01
1
OA
AI
Van-Doan Nguyen; Tien-Lam Pham; Dam, Hieu-Chi
分享
收藏
Learning structure-property relationship in crystalline materials: A study of lanthanide-transition metal alloys
JOURNAL OF CHEMICAL PHYSICS
IF
3.1
2018-05-24
30
PRE
AI
Tien-Lam Pham; Nguyen-Duong Nguyen; Van-Doan Nguyen; Kino, Hiori; Miyake, Takashi; Dam, Hieu-Chi
分享
收藏
Using community preference for overcoming sparsity and cold-start problems in collaborative filtering system offering soft ratings
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS
IF
6.3
2017-11-01
26
PRE
AI
Van-Doan Nguyen; Sriboonchitta, Songsak; Van-Nam Huynh
分享
收藏
Two-probabilities focused combination in recommender systems
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
IF
3
2017-01-01
16
OA
AI
Van-Doan Nguyen; Van-Nam Huynh
分享
收藏
Split Learning Without Local Weight Sharing to Enhance Client-Side Data Privacy
无本地权重共享的联邦学习以增强客户端数据隐私
IEEE Transactions on Dependable and Secure Computing
IF
7.5
0
PRE
AI
Ngoc Duy Pham; Khoa T. Phan; Alsharif Abuadbba; Yansong Gao; Van-Doan Nguyen; Naveen Chilamkurti
分享
收藏
研究方向
暂时未获取到该数据
合作学者
合作期刊
N
Naveen Chilamkurti
H 指数: 56 · 论文数: 355
T
Takashi Miyake
H 指数: 44 · 论文数: 239
V
Van‐Nam Huynh
H 指数: 34 · 论文数: 338
H
Hiori Kino
H 指数: 32 · 论文数: 163
S
Songsak Sriboonchitta
H 指数: 31 · 论文数: 537
查看更多