We welcome you to participate in The 2nd International Conference on Soft Computing in Data Science (SCDS) 2016 which will be held in Pullman Kuala Lumpur, Bangsar, Malaysia from 21-22 September 2016. The theme of the conference is ‘Science in Analytics: Harnessing Data and Simplifying Solutions’. Data science can improve corporate decision-making and performance, personalize medicine and healthcare services and improve organizations efficiency and performance. Data Science is about learning from your data. Thus, with the advancement in computer technology huge amount of data can be stored and harnessed. Data science and analytics plays an important role in various disciplines including business, medical and health informatics, social sciences, manufacturing, economics, accounting and finance.
SCDS2016 aims to provide a platform for discussions on leading edge methods and also addressing challenges, problems and issues in machine learning in data science and analytics. The role of machine learning in data science and analytics is significantly increasing in every field from engineering to life sciences and with advanced computer algorithms, solutions for complex real problems can be simplified. For the advancement of society in the 21st century, there is a need to transfer knowledge and technology to industrial applications to solve real-world problems. SCDS2016 have invited renowned international and local keynote speakers who are academia or practitioners to share their knowledge and experience in the area of machine learning in data science and analytics.
SCDS2016 aims to attract researchers who are actively engaged both in theoretical and practical aspects of Soft Computing in Data Science. The focus is on Machine Learning for Data Science and Analytics. Authors are invited to contribute to the conference by submitting articles in the following areas, but are not limited to the following topics:
• Decision tree learning
• Association rule learning
• Artificial neural networks
• Support vector machines
• Bayesian models and methods
• Inductive logic programming
• Reinforcement learning
• Representation learning
• Similarity and metric learning
• Sparse dictionary learning
• Feature Learning
• Genetic algorithms
• Visualization and Data Mining
• Fuzzy Logic
Applications include but are not limited to the following areas:
• Financial Analytics
• Business Analytics
• Customer Analytics
• Information Analytics
• Marketing Analytics
• Operations Analytics
• Sentiment analysis (or opinion mining)
• Big Data Computing
SCDS2016 accepts only high-quality papers for its conference proceedings, which are subject to a thorough & objective review process of at least 3 independent reviewers. Authors are invited to submit original unpublished manuscripts that demonstrate current research on one of the SCDS2016 topics of interest. All submissions will be handled electronically; detailed submission instructions will be provided on the conference homepage. The acceptance rate for SCDS2015 was 38%.
Authors are invited to electronically submit original research contributions in English.
• The length of submitted manuscripts should not exceed 15 pages.
• Full papers: Minimum 10 pages and Maximum 15 pages.
• Over-length charges will apply for each extra page beyond 10 pages.
All accepted conference papers will be published in the proceedings with Springer in the Communications in Computer and Information Science series which is abstracted (indexed) by DBLP, EI, Scopus and it is submitted for the inclusion in ISI Proceedings.