News


16 Jan 2021
One full paper is accepted by WWW 2021, about graph neural network for knowledge graph-aware recommendation.

23 April 2020
One full paper is accepted by SIGIR 2020, about graph neural network for recommendation.

11 Jan 2020
One full paper is accepted by WWW 2020, about knowledge graph-reinforced negative sampling.

29 April 2019
One full paper is accepted by KDD 2019, about graph neural network for knowledge-aware recommendation.

14 April 2019
One full paper is accepted by SIGIR 2019, about graph neural network for recommendation.

24 January 2019
I have successfully defended my thesis and got the PhD degree! My thesis title is "Exploiting Cross-Channel Information for Personalized Recommendation".

Xiang WANG 

Research Fellow

NExT++
School of Computing
National University of Singapore

Computing 1, Computing Drive, Singapore 117417

Email: xiangwang AT u.nus.edu
CVGoogle ScholarGitHub

Xiang Wang is now a research fellow in NExT++, School of Computing, National University of Singapore. His research interests include information retrieval, data mining, and explainable AI, particularly in recommender systems, graph learning, and social media analysis. Moreover, he has served as the PC member for top-tier conferences including SIGIR and MM, and the invited reviewer for prestigious journals including TKDE, TOIS, TKDD, and TIST.

Education

National University of Singapore (NUS)
Ph.D. in Computer Science                   July 2014 - February 2019, Singapore
Advisor: Prof. Chua Tat-Seng
Mentors: Dr. He Xiangnan and Dr. Nie Liqiang
Beihang University (BUAA)
Bachelor in Computer Science and Engineering      Sep 2010 - June 2014, Beijing
Advisor: Prof. Li Zhoujun

Experiences

Postdoc Research Fellow, National University of Singapore, February 2019 - Present
Advisior: Prof. Chua Tat-Seng (NExT++: NUS-Tsinghua-Southampton Extreme Search Center)
Research Intern, Institute of Automation, Chinese Academy of Sciences, June 2013 - February 2014
Advisior: Prof. Xu Changsheng and Dr. Fang Quan (National Lab of Pattern Recognition)

First-Author Publications Google Scholar


In the Year of 2021:


pdf
Learning Intents behind Interactions with Knowledge Graph for Recommendation
Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He & Tat-Seng Chua
WWW 2021 (Full, Accept rate: 20.6%)
  • arXiv    • Codes    • Slides   
In the Year of 2020:


pdf
Disentangled Graph Collaborative Filtering
Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu & Tat-Seng Chua
SIGIR 2020 (Full, Accept rate: 26%)
  • arXiv    • Codes    • Slides   

pdf
Reinforced Negative Sampling over Knowledge Graph for Recommendation
Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Meng Wang & Tat-Seng Chua
WWW 2020 (Full, Accept rate: 19%)
  • arXiv    • Codes    • Slides   
In the Year of 2019:


pdf
KGAT: Knowledge Graph Attention Network for Recommendation
Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu & Tat-Seng Chua
KDD 2019 (Full, Accept rate: 14.2%)
  • arXiv    • Codes    • Slides   

pdf
Neural Graph Collaborative Filtering
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng & Tat-Seng Chua
SIGIR 2019 (Full, Accept rate: 20%)
  • arXiv    • Codes    • Slides   

pdf
Explainable Reasoning over Knowledge Graph Paths for Recommendation
Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao & Tat-Seng Chua
AAAI 2019 (Full, Accept rate: 16.2%)
  • arXiv    • Codes    • Slides   
In the Year of 2018:


pdf
TEM: Tree-enhanced Embedding Model for Explainable Recommendation
Xiang Wang, Xiangnan He, Fuli Feng, Liqiang Nie & Tat-Seng Chua
WWW 2018 (Accept rate: 14.8%)
  • Codes    • Slides   
In the Year of 2017:


pdf
Item Silk Road: Recommending Items from Information Domains to Social Users
Xiang Wang, Xiangnan He, Liqiang Nie & Tat-Seng Chua
SIGIR 2017 (Accept rate: 22%)
  • Codes    • Slides   

pdf
Unifying Virtual and Physical Worlds: Learning towards Local and Global Consistency
Xiang Wang, Liqiang Nie, Xuemeng Song, Dongxiang Zhang & Tat-Seng Chua
ACM Transactions on Information Systems (TOIS)
  • Codes    • Slides  
Look for the full publication list? Please see my CV or visit Google Scholar.

Tutorials


pdf
Bias Issues and Solutions in Recommender System
Jiawei Chen, Xiang Wang, Fuli Feng & Xiangnan He
WWW 2021    Slides (2021/04)   

pdf
Learning and Reasoning on Graph for Recommendation
Xiang Wang, Xiangnan He & Tat-Seng Chua
WSDM 2020    Slides (2020/01 @ Houston, Texas, US)   

pdf
Learning and Reasoning on Graph for Recommendation
Xiang Wang, Xiangnan He & Tat-Seng Chua
CIKM 2019    Slides (2019/11 @ Beijing, China)   

Honors

Dean’s Graduate Research Excellence Award,   June 2018   
- School of Computing, National University of Singapore
Research Achievement Award,   June 2017   
- School of Computing, National University of Singapore
Full Research Scholarship,   2014-2019   
- National University of Singapore
Excellent Graduates,   May 2014   
- Beihang University, China
National Scholarship (top scholarship for Chinese undergraduates),   December 2013   
- Beihang University, China

Invited Talks

Explainable Reasoning over Knowledge Graph Paths for Recommendation   
- Shandong University, Augest 11, 2018 (invited by Prof. Nie Liqiang)
TEM: Tree-enhanced Embedding Model for Explainable Recommendation   
- 6estate Company, Singapore, October 11, 2018 (invited by Dr. Luan Huanbo & Dr. Wang Chao)
- WWW 2018, Lyon, France, April 26, 2018
Item Silk Road: Recommending Items from Information Domains to Social Users   
- Shandong University, May 20, 2017 (invited by Prof. Nie Liqiang)
- SIGIR 2017, Tokyo, Japan, August 5, 2017

Professional Services

Program Committee Member of KDD (2021)
Program Committee Member of WWW (2020,2021)
Program Committee Member of ACM SIGIR (2019,2020,2021)
Program Committee Member of ACM MM (2019,2020)
Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE)
Invited Reviewer for ACM Transactions on Information Systems (TOIS)
Invited Reviewer for ACM Transactions on Intelligent Systems and Technology (TIST)
Invited Reviewer for ACM Transactions on Knowledge Discovery from Data (TKDD)
Invited Reviewer for Information Sciences
Invited Reviewer for Neurocomputing
Invited Reviewer for Frontiers of Computer Science
Invited Reviewer for World Wide Web Journal (WWWJ)
Invited Reviewer for Multimedia Systems Journal (MMSJ)
External Reviewer of SIGIR 2016-2018, WWW 2017-2019.

Useful Links

NUS CS Conference Rankings
NUS CS Journal Ranking
NUS CS Courses
Machine Learning Reading List
Deep Learning Reading List

Last update: May 1, 2019. Webpage template borrows from Xiangnan He.