The 2nd workshop of Heterogeneous Information Network Analysis and Applications


  Now we are living in an interconnected world, where most of data or informational objects, agents, or components are interconnected or interact with each other, forming gigantic and sophisticated information networks. Most real-world applications based on information networks can be structured into heterogeneous information networks that include different types of objects or links. Recent work on heterogeneous information network analysis and its applications have led to a convergence of methodologies for network modeling, graph mining, linking analysis, data semantics mining, and incorporating classification, learning and reasoning with graphical models. As a promising network analysis paradigm, heterogeneous information network analysis also faces challenges, such as how to manage more complex heterogonous data like RDF data and how to quickly handle real huge heterogonous information network.
  The emphasis of this workshop shall be analysis approaches and applications based on heterogeneous information networks extracted from heterogeneous sources such as technical literature, news articles, social network profile data, and social media. However, the scope is not limited to any particular approach to link analysis or any source of network information such as text corpora. This workshop shall help to bring together people from these different areas and present an opportunity for researchers and practitioners to share new techniques for identifying and analyzing relationships in networks that integrate multiple types or sources of information.


  Topics of interest include but not limited to:

1. Heterogeneous information network construction from complex data
2. Semantic mining on heterogeneous information networks
3. Data mining methods (e.g., clustering, classification and recommendation) for heterogeneous information networks
4. Information diffusion and behavioral modeling on heterogeneous networks
5. Graph mining on heterogeneous information networks
6. Data mining based on knowledge graphs
7. Community detection and evolution of network
8. Parallel computing for information network analysis
9. Network analysis based applications for e-commerce, security, software engineering


  Paper submissions should be formatted according to the ICDSC Conference instructions. The review process is single-blind peer review (reviewers are anonymous, but authors are not). Papers that have been published elsewhere, are currently under review, or will be submitted to other meetings or publications while under HENA review should not be submitted to HENA. To submit a paper, please send a PDF version of your paper to ( We also welcome attendance of those who do not wish to submit a paper.


  Full paper due: April 3, 2016
  Acceptance notification: April 18, 2016
  Camera-ready copy: April 23, 2016
  Conference Date: June 13, 2016


General CO-Chair
Chuan ShiBeijing University of Posts and Telecommunications, China
Bin WuBeijing University of Posts and Telecommunications, China
Xiaoli LiInstitute for Infocomm Research, , A*STAR, Singapore

Program Committee

Yueguo ChenRenmin University of China, China
Jiuming Huang, National University of Defense Technology, China
Fuzheng ZhuangInstitute of Computing Technology, Chinese Academy of Sciences, China
Xi ZhangBeijing University of Posts and Telecommunications, China
Hongxin HuClemson University, USA
Shenghua LiuInstitute of Computing Technology, Chinese Academy of Sciences, China
Xiangnan KongWorcester Polytechnic Institute, China
Zhaohui Peng Shandong University, China
Zhi WeiNew Jersey Institute of Technology, China
Yun XiongFudan University, China
Zhenyu YanAdobe Systems Inc.
Ning YangSichuan University, China
Senzhang WangBeihang University, China
Xin LiBeijing Institute of Technology, China