Applied Soft Computing for Business Analytics

“Data is the new oil” is just one of the sayings that describe the importance of data for today´s society. We have witnessed a rapid development of methods to analyze such data; starting with Statistics in the early 18th century, followed by Artificial Intelligence and Machine Learning, and finally leading to Data Science incorporating classical methodologies for data analysis, advanced data storage, visualization, and new programming paradigms. Many users in business-related areas, such as finance, marketing and operations; as well as in various other fields, such as astronomy, health, security, to name just a few, got aware of the respective potential and need data-driven solutions for their problems.

In parallel, techniques for soft computing lately received increasing attention inspired by recent developments, such as Deep Learning, the recurrence of Artificial Intelligence, and new programming paradigms from Evolutionary Computation, among others.

This special issue aims to stimulate a scientific discussion on the potential of soft computing approaches for data driven solutions, providing a platform for top-level publications showing how Applied Soft Computing can be used for Business Analytics.

Topics relevant for this special issue include, but are not limited to:

Business Analytics – Methods:

– Dimensionality Reduction, Feature Extraction, and Feature Selection
– Supervised, Semi-Supervised, and Unsupervised Methods
– Statistical Learning Theory
– Online Learning, Data Stream Mining, and Dynamic Data Mining
– Graph Mining and Semi-Structured Data
– Spatial and Temporal Data Mining
– Deep Learning and Neural Network Research
– Large Scale Data Mining
– Uncertainty Modeling in Data Mining

Business Analytics – Applications:

– Credit Scoring and Financial Modeling
– Forecasting
– Fraud Detection
– Web Intelligence and Information Retrieval
– Marketing, Business Intelligence, and e-Commerce
– Decision Analysis and Decision Support Systems
– Social Network Analysis
– Privacy-preserving Data Mining and Privacy-related Issue
– Text Mining, Sentiment Analysis, and Opinion Mining


Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. The papers should be submitted via the journal website ( and should adhere to standard formatting requirements. Authors should select “SI: BAFI 2015” when reaching the step of selecting article type in submission process. Authors should indicate on the cover letter that the paper is intended for the Special Issue entitled “Applied Soft Computing for Business Analytics”. For additional questions, contact the Guest Editors.

 Important Dates:

– March 15, 2016: Submission deadline
– August 30, 2016: Notification of the first-round review
–  October 30, 2016: Revised submission due
– March 15, 2017: Final notice of acceptance/reject
– April 30, 2017: Final Reception of the accepted papers

Guest editors:

– Cristián Bravo, Universidad de Talca, Chile

– Rudolf Kruse, University of Magdeburg, Germany

– Sebastián Maldonado, Universidad de los Andes, Chile

– Richard Weber, Universidad de Chile, Chile
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