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We are pleased to present the proceeding of the 4th International Conference on Soft
Computing in Data Science 2018 (SCDS 2018). SCDS 2018 was held in Chulalongkorn
University, in Bangkok, Thailand, during August 15–16, 2018. The theme
of the conference was “Science in Analytics: Harnessing Data and Simplifying Solutions.”
SCDS 2018 aimed to provide a platform for highlighting the challenges faced
by organizations to harness their enormous data, and for putting forward the availability
of advanced technologies and techniques for big data analytics (BDA).
SCDS 2018 provided a platform for discussions on innovative methods and also
addressed challenges, problems, and issues in harnessing data to provide useful
insights, which results in more impactful decisions and solutions. The role of data
science and analytics is significantly increasing in every field from engineering to life
sciences, and with advanced computer algorithms, solutions for complex real-life
problems can be simplified. For the advancement of society in the twenty-first century,
there is a need to transfer knowledge and technology to industrial applications to solve
real-world problems that benefit the global community. Research collaborations
between academia and industry can lead to the advancement of useful analytics and
computing applications to facilitate real-time insights and solutions.
We were delighted to collaborate with the esteemed Chulalongkorn University this
year, and this increased the submissions from a diverse group of national and international
researchers. We received 75 paper submissions, among which 30 were
accepted. SCDS 2018 utilized a double-blind review procedure. All accepted submissions
were assigned to at least three independent reviewers (at least one international
reviewer) in order to ensure a rigorous, thorough, and convincing evaluation
process. A total of 36 international and 65 local reviewers were involved in the review
process. The conference proceeding volume editors and Springer’s CCIS Editorial
Board made the final decisions on acceptance with 30 of the 75 submisssions (40%)
published in the conference proceedings. Machine learning using LDA (Latent
Dirichlet Allocation) was used on the abstracts to define the track sessions.
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