Knowledge Enhanced Data Analytics for Autonomous Decision Making

  in Special Issue   Posted on March 24, 2020

Information for the Special Issue

Special Issue Call for Papers:

Aim and Scope

In today’s world, we are aware that how breakthroughs in data analytics and high-performance computing has made society-changing AI applications in different areas. One particular stand out success relates to learning from a massive amount of data in real time to quickly identify newly emerging unknown patterns. However, successful decision-making analysis must combine the best qualities of both human analysts and computers, while the challenge is how to structure relevant and reliable knowledge and incorporate them as part of decision analytics. On the one hand, decision making needs the context, organization, and consistency that analytics by itself does not provide. There is increasing recognition for utilizing knowledge whenever it is available or can be created purposefully. On the other hand, autonomous decision-making and the black-box design of machine learning make the adoption of AI systems complicated and has led to resurgence in interest in explainability of AI systems.

This Special Issue aims to demonstrate the indispensable role of business, data and methodological know-how in helping decision-making and how to use and exploit the prior knowledge to enhance data analytic for autonomous decision-making.

 

Topics

We are seeking both conceptual and empirical papers offering new insights and contribution to the development of data analytic algorithms and systems for autonomous decision-making, which focus on the following topics (but are not limited to) which demonstrate the role of exploiting the knowledge to enhance data analytics:

• Application that have limited data;

• Applications require safety or stability guarantees;

• Applications while large amounts of quality training data are unavailable;

• Application while the objects to be recognized are complex, (e.g., implicit entities and highly subjective content);

• Applications need to use complementary or related data in multiple modalities/media;

• Enhancing the capability in handling uncertainty;

• Enhancing transparency, interpretability and explainability;

• Reducing the complexity of model architecture in time and space;

• Enhancing the capability to avoid social discrimination and unfair treatment;

• Enhancing automated decision making capability and performance;

• Enhancing reliability and integrity of data analytics.

This Special Issue will open to all submissions which are original and not previously published or currently submitted for journal publication elsewhere, must fit this special issue theme and must clearly delineate the role of knowledge in enhancing the data analytics for decision making purpose. We encourage researchers to innovate new solutions to the key problems in this emerging field. In general, we do not accept survey papers.

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.

 

Instructions for Manuscripts

Submissions must be directly sent via the IJAR submission web site at https://www.journals.elsevier.com/international-journal-of-approximate-reasoning.

Paper submissions must conform to the layout and format guidelines in the IJAR. Instructions for Authors are in: https://www.elsevier.com/journals/international-journal-of-approximate-reasoning/0888-613x/guide-for-authors.

During the submission process, please select the category of SI: KEDA for DM as the article type.

 

Important Dates

Manuscript Due: April 30, 2020

First notification: July 30, 2020

Submission of revised manuscript: September 15, 2020

Final notification: October 31, 2020

Submission of final papers: November 20, 2020

Publication Date: to be scheduled in 2021

 

 

Guest Editors:

Dr Jun Liu

Ulster University, United Kingdom

Email: j.liu@ulster.ac.uk

Dr Rosa M Rodríguez

University of Jaen, Spain

Email: rmrodrig@ujaen.es

Prof. Hui Wang

Ulster University, United Kingdom

Email: h.wang@ulster.ac.uk

 

Submission plan

To aid planning and organization, please e-mail to Guest Editors a short note of your intention to submit a paper as early as possible by 18th of February 2020 including the following items:

  • author information
  • a tentative title
  • abstract, and
  • an estimated number of pages

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