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ESSFA 2018 : Expert Systems: Smart Financial Applications in Big Data Environments

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Link: https://easychair.org/cfp/ESSFA2018
 
When Jan 30, 2018 - Jun 30, 2018
Where USA
Abstract Registration Due Jun 1, 2018
Submission Deadline Jun 15, 2018
Notification Due Jul 1, 2018
Final Version Due Jul 15, 2018
Categories    book chapter   expert systems applications   financial big data analysis   intelligent systems
 

Call For Papers

Call for Book Chapter
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Expert Systems: Smart Financial Applications in Big Data Environments
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Publication
ESSFA2018 will be published by Taylor & Francis

Contact
All questions about submissions should be emailed to mohamed_elhoseny@mans.edu.eg or mohamed.elhoseny@unt.edu
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In order to reduce the risk of human mistakes in financial domains, expert systems have gained a great advantage in big data environments. Besides their efficiency in quantitative analysis such as profitability, banking management, and strategic financial planning, expert systems have successfully treated qualitative issues including financial analysis, investments advisories, and knowledge based decision support systems. Due to the increase in financial applications size, complexity and the number of components, it is no longer practical to anticipate and model all possible interactions and data processing in these applications using the traditional data processing model. The emerging of new engineering research areas is a clear evidence of the emergence of new demands and requirements of modern real-life applications to be more intelligent. Recently, expert systems with explanation for decision making can achieve a high accuracy rate to support financial institutions in a highly volatile climate. It is being promoted by the software engineering community to use such systems as the adequate solution to handle the current requirements of complex big data processing problems that demanding distribution, flexibility, and robustness.

The main objective of this book is to provide an exhaustive review on the roles of expert systems in financial sectors with special reference to big data environments. In addition, it aims to provide a collection of high quality research works that address broad challenges in both theoretical and application aspects of intelligent and expert systems in finance. We invite colleagues to contribute original book chapters that will stimulate the continuing effort on the application of the intelligent systems that leads to solve the problem of big data processing in a smart banking and financial environment. We invite all researchers and practitioners who are developing algorithms, systems, and applications, to share their results, ideas, and experiences.



Submission Guidelines
Submitted manuscripts should conform to the standard guidelines of the Taylor & Francis book chapter format. Manuscripts must be prepared using Latex, or MS Word. Prospective authors should submit their manuscripts electronically through easychair submission system or email through this email: [ Mohamed_elhoseny@mans.edu.eg , Mohamed.elhoseny@unt.edu] Submitted manuscripts will be refereed by at least two independent and expert reviewers for quality, correctness, originality, and relevance.

List of Topics
Intelligent Algorithms in Finance
Big data analysis in financial applications.
Internet of Things (IoT) Application in Financial management
Intelligent Investment Advisory
Optimization Algorithms for portfolio selection
Expert systems in banking management
Smart models of strategic financial planning
Decision Support Systems in financial domains
Secure data processing in financial applications
Smart applications of forint exchange trading
Big Data Economy, QoS and Business Models
Big Data analytics for customer value creation.
Evolutionary Computing Algorithms for Financial Applications
Swarm Intelligence for Business Applications
Genetic Algorithm for Business Applications
Big Data Quality and Management for Business Applications
Financial Analysis for Mobile and Cloud Applications
Business Intelligence Applications for Finance
Customer Segmentation or Profiling
Utility-Based Data Mining in Business Applications
Intelligent Distributed Applications in E-Commerce, E-Health, E-Government
Volume Editors
Prof. Aboul Ella Hassanien: Faculty of Computers & Information, Cairo University, Egypt, Aboitcairo@gmail.com

Prof. M. Kabir Hassan: Department of Economics and Finance, University of New Orleans, USA, mhassan@uno.edu

Dr. Mohamed Elhoseny: Faculty of Computers and Information, Mansoura University, Egypt, Mohamed_elhoseny@mans.edu.eg

Dr. Noura Metawa: Department of Economics and Finance, University of New Orleans, USA, nsmetawa@uno.edu



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