Indexing:

Call for papers for a Special Issue

Long title

Advance Mathematics and applications in Big Data Analytics

Acronym

AMABDA

Short description

This special issue will address inventive methodologies in the general region of business knowledge and information mining just as explicit methodologies managing the subject enormous information and web information mining in the movement and the mathematics filed. With the approach of new advancements like Internet of Things, correspondence innovations, and wide assortment of online networking applications, associations produce colossal volumes of information in brought together configurations. Breaking down such information and picking up choice applicable information is imperative for any sort of partner, for example, governments, associations, and networks. Therefore, applying strategies from business insight and information mining to extricate applicable information from accessible information sources comprises a significant vein of exploration in the field of large information and business knowledge. Large information investigation that find bits of knowledge from proof has popularity for figuring productivity, information disclosure, critical thinking, and occasion remedy. As of late, the term enormous information has been authored, which is portrayed with high volume, assortment and speed, progressively drives dynamic and is changing the scene of business insight. Because of the critical job and significance of internet based life and online item audits, the above patterns become indispensable for different partners to guarantee seriousness and, in this manner, as of now increased high exploration consideration.

The main scope of this special issue is to help researchers in blending machine learning with mathematical application. It also focuses on major challenges and trends in this area to identify new state of art techniques used in business intelligence in real time scenario.

Potential topics of interest include, but are not limited to the following: 
‒        Innovative methods for big data analytics
‒        Mathematics oriented application and case student
‒        Techniques for mining unstructured, spatial-temporal, streaming and/or multimedia data
‒        Machine learning from big data
‒        Parallel, accelerated, and distributed big data analytics
‒        Value and performance of big data analytics
‒        Data visualization
‒        Numerical Analysis
‒        Predictive and Prescriptive Modeling
‒        Real-world applications of big data analytics, such as default detection, cybercrime, e-commerce, ehealth etc.
‒        Security and privacy in big data era

Guest editor(s)

 

Dr. K. Vengatesan ,B.E., M. Tech., Ph.D., Professor,
Department of Computer Engineering,
Sanjivani College of Engineering,
Kopargaon, Ahmednagar (D.T),
Maharashtra, Kopargaon-423 603, India.
E-mail: kvengatesancomp@sanjivani.org.in

Dr. Abhishek Kumar
Department of Computer Science
Banaras Hindu University,
Varanasi, UP, India.
E-mail: abhishek.maacindia@gmail.com

Deadline for submission of papers

Manuscript submissions due                     (30/08/2020)
First round of reviews completed             (15/09/2020)
Revised manuscripts due                            (25/09/2020)
Second round of reviews completed         (30/09/2020)
Final manuscripts due                                 (10/10/2020)

E-mail for submission of papers

amabdresearch@gmail.com