Call for Papers: Special Issue on Domain-Driven Data Mining

Guest Editors

Chuanren Liu
The University of Tennessee, Knoxville, USA
cliu89@utk.edu

Tong Xu
University of Science and Technology of China, Hefei, China
tongxu@ustc.edu.cn

Ehsan Fakharizadi
Indeed.com, San Francisco, USA
e.fakhar@gmail.com

Philip S. Yu
University of Illinois at Chicago, Chicago, USA
psyu@cs.uic.edu


Aims and Scope
Data mining has been a trending research area with contributions from diverse communities including computer scientists, statisticians, mathematicians, and researchers working on data-intensive problems. While most data mining methodologies are developed for general problem settings, such as unsupervised learning and supervised learning, (1) there are many factors and challenges such as socioeconomic, organizational, human-centered and cultural aspects rarely explored; (2) there are also specific domain knowledge, factors and challenges in developing data mining solutions for a specific domain or a novel real-world application; and (3) a critical challenge facing existing data mining is to discover actionable knowledge that can directly support decision-making tasks. Due to the need of incorporating such domain knowledge, factors and challenges in the data mining process, the challenge to discover actionable knowledge hidden in complex data, and the lack of both general and customized algorithms and tools, domain driven data mining presents many significant challenges and opportunities for transforming data mining to actionable knowledge discovery and for delivering actionable insights and intelligence for solving general and specific domain-driven problems. This special issue aims to call for the latest theoretical and practical developments, expert opinions on the open challenges, lessons learned, and best practices in domain driven data mining.

Topics of Interest
We solicit original, unpublished and innovative research work on all aspects around, but not limited to, the following themes:

  • Domain knowledge-guided data collection and processing
  • Domain knowledge and factor representation
  • Socio-economic factor modeling for data mining
  • Cultural and language modeling for data mining
  • Organizational factor modeling for data mining
  • Human intelligence for data mining
  • Ubiquitous intelligence for data mining
  • Domain-driven knowledge graph
  • Domain-driven multi-modal data mining
  • Cross-domain/multi-domain learning
  • Cross-domain recommender systems
  • Consumer behavior mining and recommender systems
  • Customer relationship management and data mining
  • Mobile-commerce and ubiquitous computing
  • Data mining for FinTech, electronic auctions and supply chain management
  • Data mining for e-government and corporate analytics
  • Data mining for economic and management science research
  • Data mining for social good
  • Knowledge actionability and actionable knowledge discovery
  • Emerging technologies and technological innovation
  • Ethics, privacy, security and explanability in data mining
  • Evaluation strategies and methods with domain expertise and satisfaction
  • Best practice of domain-specific data mining applications

Important Dates
Submission Deadline: July 1, 2021
First Notification: September 1, 2021
Revisions Due: October 1, 2021
Final Notification: December 1, 2021
Final Manuscript: December 31, 2021

Submission Guidelines

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process. Manuscripts will be subject to a peer reviewing process and must conform to the author guide lines available on the JDSA website at: https://www.springer.com/41060.

Author Resources

Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals.  

All papers will be reviewed following standard reviewing procedures for the Journal. 

Papers must be prepared in accordance with the Journal guidelines: www.springer.com/41060

Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources page, including FAQs,  Tutorials along with Help and Support.

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