CfP: Decision Making in Heterogeneous Network Data Scenarios and Applications
Decision making is the process of making choices by identifying a decision, gathering information, and assessing alternative resolutions. Using a step-by-step decision-making process can help customers make more deliberate, thoughtful decisions by organizing relevant information and defining alternatives. Traditionally, decision making has been investigated in recommendation in social networks, autonomous operations in multi-agent environments, production planning and scheduling in manufacturing systems, patientsí care and treatment in emergency department management in hospitals. However, nowadays, the data used for decision making analysis is often linked and it is in the form of heterogeneity. These heterogeneous relationships may be implicit and cannot be directly processed using the traditional approaches. Therefore, this special issue will establish an emerging forum to attract high-quality research submissions from worldwide scholars to solve the new challenges of making smart decisions in heterogeneous network data scenarios and applications.

Aims and Scope

Existing studies on heterogeneous network data mainly include link prediction, network embedding/representation learning, node classification and clustering, and recommendation problems. There are few researches to discuss how these techniques can be extended to support decision making in heterogeneous network data scenarios and applications. This special issue will encourage researchers to pay more attention to the significant research gap, and deliver practical solutions for making decision in real-life applications. Therefore, this special issue will focus on emerging techniques of decision making in the heterogeneous network data scenarios, and advance applications of decision making in complex situations.

Topics of Interest

The topics of this special issues include but not limited to:

Group decision in social recommendation
Sequential choices in decision making for e-commerce
Predictive decision making in incomplete data scenarios
Dynamic decision making in data streaming environments
Trust based decision making in hostile environments
Cross-types decision making in heterogeneous network data scenarios
Multi-criteria decision making in heterogeneous network data applications
Personalised behaviour engagement in decision learning and making
New knowledge discovery in decision making process
Knowledge driven decision making in heterogeneous network data
Benchmark studies of decision-making frameworks and algorithms
Important Dates

Submissions open: July 15, 2021

Submission deadline: October 15, 2021

First review notification: December 14, 2021

Resubmission of revised manuscripts: January 31, 2022

Final notification due: March 20, 2022

Camera ready deadline: May 15, 2022

Guest Editors

Associate Professor Jianxin Li, Deakin University, Australia (jianxin.li@deakin.edu.au)

Professor Chengfei Liu, Swinburne University of Technology, Australia (cliu@swin.edu.au)

Professor Ziyu Guan, Xidian University, China, (zyguan@xidian.edu.cn)

Assistant Professor Yinghui Wu, Case Western Reserve University, USA, yxw1650@case.edu