News


21 Dec. 2016
Two full papers are accepted by WWW 2017. One is about Neural Collaborative Filtering and the other very solid work with Steffen Rendle is about Factorization Machines for Implicit Feedback

15 Nov. 2016
One paper about App Recommendation is accepted by Transactions on Information Systems (TOIS) as a full paper.

11 Nov. 2016
I am invited to be a program committee member (full paper) in SIGIR 2017.

5 Nov. 2016
I am invited to be a program committee member (short paper) in SIGIR 2017.

14 Sep. 2016
Our work BiRank: Towards Ranking on Bipartite Graphs is accepted by Transactions on Knowledge and Data Engineering (TKDE) as a full paper.


20 July 2016
I succefully present our two papers in SIGIR 2016. The Discrete CF paper achieves the Best Paper Award Honorable Mention!

05 July 2016
I am invited to be the reviewer of World Wide Web Journal (WWWJ)..

22 June 2016
Two papers have been accepted to ACMMM 2016 as full research paper! One is about contextual image-tweet recommendation and the other is about venue prediction from micr-videos.

30 March 2016
Two papers have been accepted to SIGIR 2016 as full research paper! One is about fast matrix factorization for implicit feedback and the other is about discrete hashing for collaborative filtering.

24 March 2016
I have successfully defended my thesis and got the PhD degree! My thesis title is "Exploiting User Comments for Web Applications".

7 March 2016
I am invited to be a program committee member in EMNLP 2016.

23 Jan. 2016
I am invited to be a program committee member (short paper) in SIGIR 2016.

2 Dec. 2015
I am invited to be the reviewer of Journal of Information Science.

22 Oct. 2015
I presented my work about review-aware recommendation at CIKM'15 Melbourne, check the slides here!

25 Sep. 2015
My summer internship in Google research successfully finishes. Many thanks to my hosts Bhargav Kanagal and Steffen Rendle!

16 Aug. 2015
I am invited to be a program committee member in WWW 2016 .

4 Jul. 2015
Our full paper "Review-aware Explainable Recommendation by Modeling Aspects" is accepted by CIKM 2015.

22 Jun. 2015
I start my summer internship in Google MTV office. Enjoy the summer at the Bay area!

24 Apr. 2015
My thesis proposal "Mining Web 2.0 User Comments" passes. I am expected to graduate (submit thesis) on Dec. 2015.

3 Mar. 2015
I am invited to be the reviewer of Journal of Web Engineering.

Xiangnan HE 

Research Fellow

Lab for Media Search
School of Computing
National University of Singapore

Computing 1, Computing Drive, Singapore 117417

Email: xiangnanhe at gmail dot com

I am currently a postdoctoral research fellow with Prof. Chua Tat-Seng since April 2016. Prior to that, I did my Ph.D. with Prof. Kan Min-Yen from August 2011 to March 2016. My research interests span information retrieval (IR), machine learning (ML), natural language processing (NLP) and multi-media (MM). I serve as the PC member for the prestigious conferences including SIGIR, WWW and EMNLP.

Currently, I am working on 1) developing recommender algorithms for social groups, 2) designing deep learning methods for predictive analytics.

Before coming to Singapore, I obtained my bachelor degree in Software Engineering Institute, East China Normal University(Shanghai, China) from 2007 to 2011. I was advised by Prof. Cheqing Jin and Prof. Aoying Zhou for my undergraduate research. In addition, I was an intern at Google Research, Microsoft and Accenture. Here is my CV.

Internships

Google Research
Research Intern, Strategic Technology Group, supervised by Bhargav Kanagal and Steffen Rendle.
Mountain View, United States    Jun. 2015 - Sep. 2015
Google Inc.
Software Engineering Intern, Local Search Group, supervised by Thomas Sidoti and Sheng Zhang.
New York City, United States    Jun. 2014 - Sep. 2014
Microsoft Inc.
Software Engineering Intern, Operating System Group.
Shanghai, China    Sep. 2010 - Dec. 2011
Accenture Inc.
IT Consult Intern, Media Markt project.
Shanghai, China    Jan. 2011 - Apr. 2011

Publications


pdf
Neural Collaborative Filtering
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu & Tat-Seng Chua
WWW 2017 (Accept rate: 17%)    Codes

pdf
A Generic Coordinate Descent Framework for Learning from Implicit Feedback
Immanuel Bayer*, Xiangnan He*, Bhargav Kanagal & Steffen Rendle
WWW 2017 (Accept rate: 17%)    *Joint work at Google.

pdf
BiRank: Towards Ranking on Bipartite Graphs
Xiangnan He, Ming Gao, Min-Yen Kan & Dingxian Wang
IEEE Transactions on Knowledge and Data Engineering (TKDE 2017)   

pdf
Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts
Da Cao, Xiangnan He, Liqiang Nie, Xiaochi Wei, Xia Hu, Shunxiang Wu & Tat-Seng Chua
ACM Transactions on Information Systems (TOIS 2017)    Codes

pdf
Version-sensitive mobile App recommendation
Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Jialie Shen, Shunxiang Wu & Tat-Seng Chua
Information Science (2017)    Codes

pdf
Fast Matrix Factorization for Online Recommendation with Implicit Feedback
Xiangnan He, Hanwang Zhang, Min-Yen Kan & Tat-Seng Chua
SIGIR 2016.   (Accept rate: 18%)    Codes    Slides

pdf
Discrete Collaborative Filtering
Hanwang Zhang, Fumin Shen, Wei Liu, Xiangnan He, Huanbo Luan & Chua Tat-Seng
SIGIR 2016.   (Accept rate: 18%)    Codes    Slides (Best Paper Award Honorable Mention)

pdf
Context-aware Image Tweets Modelling and Recommendation
Tao Chen, Xiangnan He & Min-Yen Kan
MM 2016.   (Accept rate: 20%)    Codes

pdf
Shorter-is-Better: Venue Category Estimation from Micro-Video
Jianglong Zhang, Liqiang Nie, Xiang Wang, Xiangnan He, Xianglin Huang & Tat-Seng Chua
MM 2016.   (Accept rate: 20%)    Codes

pdf
TriRank: Review-aware Explainable Recommendation by Modeling Aspects
Xiangnan He, Tao Chen, Min-Yen Kan & Xiao Chen
CIKM 2015.   (Accept rate: 18%)    Slides

pdf
Relating an Image Tweet’s Text and Images
Tao Chen, Hany M. SalahEldeen, Xiangnan He, Min-Yen Kan & Dongyuan Lu
AAAI 2015.   (Accept rate: 26.7%)    Codes

pdf
 
Predicting the Popularity of Web 2.0 Items Based on User Comments
Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu & Kazunari Sugiyama
SIGIR 2014.   (Accept rate: 21%)   Slides

pdf
Comment-based Multi-View Clustering of Web 2.0 Items
Xiangnan He, Min-Yen Kan, Peichu Xie & Xiao Chen
WWW 2014.   (Accept rate: 12.9%) Supplement  Slides  Codes

pdf
Mining Scientific Terms and their Definitions: A Study of the ACL Anthology
Yiping Jin, Min-Yen Kan, Jun-Ping Ng & Xiangnan He
EMNLP 2013.   (Accept rate: 27%)   Poster  Dataset

pdf
Recording How-Provenance on Probabilistic Databases
Ming Gao, Xiangnan He, Cheqing Jin, Xiaoling Wang & Aoying Zhou
APWEB 2010.

Datasets

Multi-View Clustering with User Comments
The first public user comments dataset for multi-view clustering. The groundtruth labels are provided as the categories of items. The textual comments have been pre-processed, include stemming, removing stopwords .etc.
WWW 2014 paper.

Teaching Assistants

CS5228 Knowledge Discovery and Data Mining
2014/2015 Semester 1
CS3245 Information Retrieval
2013/2014 Semester 2
CS3245 CS1020 Data Structure and Algorithms
2013/2014 Semester 1

Useful Links

NUS SoC Conference Rankings
NUS SoC Journal Ranking
NUS SoC Courses
Mallet (MAchine Learning for LanguagE Toolkit)
Machine Learning Reading List
Deep Learning Reading List

Last update: December 21, 2016. Webpage template borrows from Weinan Zhang.