ICGCIoT 2016 | 10-12 November 2016


Welcome to DS & BDA 2018!

The International Symposium on Data Science and Big Data Analytics (DS & BDA 2018) is pleased to invite you to respond to our Call for Submissions for ICGCIoT 2018, 16-18 August 2018 at theGlobal Academy of Technology (Global Academy of Technology), Bangalore, Karnataka.

The staggeringly swift spurt in the development of IT technology including Internet, Cloud Computing, Mobile Computing and Internet of Things and its resultant decrease of cost on collecting and storing data has facilitated generation of big data from almost every industry and sector as well as government department. The exponential growth of big data is astoundingly incalculable and immeasurable beyond the bounds of Moore’s law. This growth also paved the way for the extension of traditional structured data into semi-structured and completely unstructured data of various types, such as text, image, audio, video, click streams, log files, etc.,

While big data offers us with blessings of unequalled opportunities it is also fraught with equally several challenges. Its massive volume and inherent complexity is extremely difficult to store, aggregate, manage and analyze big data and finally mine valuable information / knowledge from the complex data / information networks. Therefore, in the presence of Big data, the theories, models, algorithms and methods of traditional data related fields, such as, data mining, data engineering, machine learning, statistical learning, computer programming, pattern recognition and learning, visualization, uncertainty modeling and high performance computing etc., becomes no longer effective and efficient. On the other hand, some data is generated exponentially or super-exponentially in a streaming manner. In the context of such complexity, what looms before us as an insurmountable challenge is how to delicately analyze and deeply understand big data so as to obtain dynamical and incremental information / knowledge. In general, the era of big data envisages a period of phenomenal development to usher in new theories, models, algorithms, methods and paradigms for mining, analyzing, and understanding big data and even a new inter-discipline, Data Science, for studying the perception, acquisition, transportation, storage, management, analysis, visualization and applications of big data and finally implement the transformation from data to knowledge.

Technical Committee

Dr. S. Senthil, Director, School of Computer Science and Applications, REVA University, Bangalore, India (Chair(s))

Dr. Ayman EL-Sayed, Professor, Computer Science and Engineering Department, Menouf, Egypt
Dr. Alaa Shtay, Associate Professor, Dept. of Computer Science and Information Systems, College of Science, Shaqra University, KSA
Dr. T. Sivaramu, Nizwa College of Technology, Oman
Dr. Boopathi Gopalkrishnan, Professor, Faculty of Engineering and Applied Sciences, Botho university, P.O 501564, Gaborone, Botswana
Dr. R. Nadarajan, Professor, Department of Applied Mathematics with Computational Sciences, PSG College of Technology, Coimbatore, India
Dr. V. Ilango, Professor and Head, Department of MCA, New Horizon College of Engineering, Bangalore
Dr. L. Robert, Reader, Government Arts College, Coimbatore
Dr. E. Karthikeyan, Professor, Government Arts College, Udumalpet
Dr. T. Arunkumar, Professor and Dean, School of Computer Science and Engineering, VIT University, Vellore, Tamilnadu
Dr. R. Manoharan, Professor, Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry
Dr. R Rajesh, Associate Professor & Head, Department Of Computer Science, Central University of Kerala, Kerala
Dr. Antony Franklin, Assistant Professor, Department of Computer Science and Engineering, IIT, Hyderabad
Dr. Ka. Selvaradjou, Professor, Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry
Dr. J. Satheesh Kumar, Associate Professor, School of Computer Science and Applications, Bharathiar University, Coimbatore
Dr. Shirshu Varma, Associate Professor, Indian Institute of Information Technology, Allahabad
Dr. R. Anand, Associate Professor, Department of MECS, NITK, Suratkkal, Mangalore
Dr. Deepa Anand, Professor, Department of MCA, CMR Institute of Technology, Bangalore
Dr. R. Chinnayan, Professor, Department of MCA, New Horizon College of Engineering, Bangalore
Dr. G.N.K Suresh Babu, Associate Professor, Acharya Institute of Technology, Bangalore

Topics

  • Acquisition, Representation, Indexing, Storage and Management of Big Data
  • Processing, Pre-processing and post-processing of big data
  • Visualizing analytics and organization of big data
  • Context data mining from big web data
  • Social computing over big web data
  • Industrial and scientific applications of big data
  • Tools for big data analytics
  • Data Visualization and Visual Analytics
  • Natural Language Processing in Big Texts
  • Scalable Computational intelligence tools
  • Novel computational intelligence approaches for data analysis
  • Evolutionary and Bio-inspired approaches for Big Data analysis
  • New domains and novel applications related to big data technologies
  • Algorithms for Large Data Sets
  • Business Intelligence
  • Cluster, Cloud, and Grid Computing
  • Data Centric Programming
  • Data Modeling and Semantic Engineering
  • Data, Text, Web Mining, and Visualization
  • Domain Specific Data Management
  • High Performance Scientific/Engineering/Commercial Applications
  • Interoperability and Data Integration using Open Standards
  • Info science and Computational Informatics
  • Information discovery and Query processing
  • Knowledge based Software Engineering
  • Knowledge Engineering
  • Machine Learning and Natural Language Computing
  • Management of very large data systems
  • Peer-to-Peer Algorithms and Networks
  • Statistical Computing
  • Web Engineering

Applications

  • Internet Search
  • Digital Advertisements (Targeted Advertising and re-targeting)
  • Recommender Systems
  • Image Recognition
  • Speech Recognition
  • Gaming
  • Airline Route Planning
  • Fraud and Risk Detection
  • Delivery logistics
  • Miscellaneous

Submission Guidelines

Submit your paper in IEEE format. Submitted work should be original and application oriented. Acceptance will be based on reviewer's comments that will address the strong and weak aspects with suggestions to improve the work.

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